Merge pull request #1870 from alalek:move_superres_contrib

modules/superres/CMakeLists.txt

+if(IOS OR WINRT)
+  ocv_module_disable(superres)
+endif()
+
+set(the_description "Super Resolution")
+if(HAVE_CUDA)
+  ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef -Wshadow)
+endif()
+ocv_define_module(superres opencv_imgproc opencv_video
+                  OPTIONAL opencv_videoio opencv_cudaarithm opencv_cudafilters opencv_cudawarping opencv_cudaimgproc opencv_cudaoptflow opencv_cudacodec
+                  WRAP python)

modules/superres/include/opencv2/superres.hpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_SUPERRES_HPP
+#define OPENCV_SUPERRES_HPP
+
+#include "opencv2/core.hpp"
+#include "opencv2/superres/optical_flow.hpp"
+
+/**
+  @defgroup superres Super Resolution
+
+The Super Resolution module contains a set of functions and classes that can be used to solve the
+problem of resolution enhancement. There are a few methods implemented, most of them are described in
+the papers @cite Farsiu03 and @cite Mitzel09 .
+
+ */
+
+namespace cv
+{
+    namespace superres
+    {
+
+//! @addtogroup superres
+//! @{
+
+        class CV_EXPORTS FrameSource
+        {
+        public:
+            virtual ~FrameSource();
+
+            virtual void nextFrame(OutputArray frame) = 0;
+            virtual void reset() = 0;
+        };
+
+        CV_EXPORTS Ptr<FrameSource> createFrameSource_Empty();
+
+        CV_EXPORTS Ptr<FrameSource> createFrameSource_Video(const String& fileName);
+        CV_EXPORTS Ptr<FrameSource> createFrameSource_Video_CUDA(const String& fileName);
+
+        CV_EXPORTS Ptr<FrameSource> createFrameSource_Camera(int deviceId = 0);
+
+        /** @brief Base class for Super Resolution algorithms.
+
+        The class is only used to define the common interface for the whole family of Super Resolution
+        algorithms.
+         */
+        class CV_EXPORTS SuperResolution : public cv::Algorithm, public FrameSource
+        {
+        public:
+            /** @brief Set input frame source for Super Resolution algorithm.
+
+            @param frameSource Input frame source
+             */
+            void setInput(const Ptr<FrameSource>& frameSource);
+
+            /** @brief Process next frame from input and return output result.
+
+            @param frame Output result
+             */
+            void nextFrame(OutputArray frame) CV_OVERRIDE;
+            void reset() CV_OVERRIDE;
+
+            /** @brief Clear all inner buffers.
+            */
+            virtual void collectGarbage();
+
+            //! @brief Scale factor
+            /** @see setScale */
+            virtual int getScale() const = 0;
+            /** @copybrief getScale @see getScale */
+            virtual void setScale(int val) = 0;
+
+            //! @brief Iterations count
+            /** @see setIterations */
+            virtual int getIterations() const = 0;
+            /** @copybrief getIterations @see getIterations */
+            virtual void setIterations(int val) = 0;
+
+            //! @brief Asymptotic value of steepest descent method
+            /** @see setTau */
+            virtual double getTau() const = 0;
+            /** @copybrief getTau @see getTau */
+            virtual void setTau(double val) = 0;
+
+            //! @brief Weight parameter to balance data term and smoothness term
+            /** @see setLabmda */
+            virtual double getLabmda() const = 0;
+            /** @copybrief getLabmda @see getLabmda */
+            virtual void setLabmda(double val) = 0;
+
+            //! @brief Parameter of spacial distribution in Bilateral-TV
+            /** @see setAlpha */
+            virtual double getAlpha() const = 0;
+            /** @copybrief getAlpha @see getAlpha */
+            virtual void setAlpha(double val) = 0;
+
+            //! @brief Kernel size of Bilateral-TV filter
+            /** @see setKernelSize */
+            virtual int getKernelSize() const = 0;
+            /** @copybrief getKernelSize @see getKernelSize */
+            virtual void setKernelSize(int val) = 0;
+
+            //! @brief Gaussian blur kernel size
+            /** @see setBlurKernelSize */
+            virtual int getBlurKernelSize() const = 0;
+            /** @copybrief getBlurKernelSize @see getBlurKernelSize */
+            virtual void setBlurKernelSize(int val) = 0;
+
+            //! @brief Gaussian blur sigma
+            /** @see setBlurSigma */
+            virtual double getBlurSigma() const = 0;
+            /** @copybrief getBlurSigma @see getBlurSigma */
+            virtual void setBlurSigma(double val) = 0;
+
+            //! @brief Radius of the temporal search area
+            /** @see setTemporalAreaRadius */
+            virtual int getTemporalAreaRadius() const = 0;
+            /** @copybrief getTemporalAreaRadius @see getTemporalAreaRadius */
+            virtual void setTemporalAreaRadius(int val) = 0;
+
+            //! @brief Dense optical flow algorithm
+            /** @see setOpticalFlow */
+            virtual Ptr<cv::superres::DenseOpticalFlowExt> getOpticalFlow() const = 0;
+            /** @copybrief getOpticalFlow @see getOpticalFlow */
+            virtual void setOpticalFlow(const Ptr<cv::superres::DenseOpticalFlowExt> &val) = 0;
+
+        protected:
+            SuperResolution();
+
+            virtual void initImpl(Ptr<FrameSource>& frameSource) = 0;
+            virtual void processImpl(Ptr<FrameSource>& frameSource, OutputArray output) = 0;
+
+            bool isUmat_;
+
+        private:
+            Ptr<FrameSource> frameSource_;
+            bool firstCall_;
+        };
+
+        /** @brief Create Bilateral TV-L1 Super Resolution.
+
+        This class implements Super Resolution algorithm described in the papers @cite Farsiu03 and
+        @cite Mitzel09 .
+
+        Here are important members of the class that control the algorithm, which you can set after
+        constructing the class instance:
+
+        -   **int scale** Scale factor.
+        -   **int iterations** Iteration count.
+        -   **double tau** Asymptotic value of steepest descent method.
+        -   **double lambda** Weight parameter to balance data term and smoothness term.
+        -   **double alpha** Parameter of spacial distribution in Bilateral-TV.
+        -   **int btvKernelSize** Kernel size of Bilateral-TV filter.
+        -   **int blurKernelSize** Gaussian blur kernel size.
+        -   **double blurSigma** Gaussian blur sigma.
+        -   **int temporalAreaRadius** Radius of the temporal search area.
+        -   **Ptr\<DenseOpticalFlowExt\> opticalFlow** Dense optical flow algorithm.
+         */
+        CV_EXPORTS Ptr<SuperResolution> createSuperResolution_BTVL1();
+        CV_EXPORTS Ptr<SuperResolution> createSuperResolution_BTVL1_CUDA();
+
+//! @} superres
+
+    }
+}
+
+#endif // OPENCV_SUPERRES_HPP

modules/superres/include/opencv2/superres/optical_flow.hpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_SUPERRES_OPTICAL_FLOW_HPP
+#define OPENCV_SUPERRES_OPTICAL_FLOW_HPP
+
+#include "opencv2/core.hpp"
+
+namespace cv
+{
+    namespace superres
+    {
+
+//! @addtogroup superres
+//! @{
+
+        class CV_EXPORTS DenseOpticalFlowExt : public cv::Algorithm
+        {
+        public:
+            virtual void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2 = noArray()) = 0;
+            virtual void collectGarbage() = 0;
+        };
+
+
+        class CV_EXPORTS FarnebackOpticalFlow : public virtual DenseOpticalFlowExt
+        {
+        public:
+            /** @see setPyrScale */
+            virtual double getPyrScale() const = 0;
+            /** @copybrief getPyrScale @see getPyrScale */
+            virtual void setPyrScale(double val) = 0;
+            /** @see setLevelsNumber */
+            virtual int getLevelsNumber() const = 0;
+            /** @copybrief getLevelsNumber @see getLevelsNumber */
+            virtual void setLevelsNumber(int val) = 0;
+            /** @see setWindowSize */
+            virtual int getWindowSize() const = 0;
+            /** @copybrief getWindowSize @see getWindowSize */
+            virtual void setWindowSize(int val) = 0;
+            /** @see setIterations */
+            virtual int getIterations() const = 0;
+            /** @copybrief getIterations @see getIterations */
+            virtual void setIterations(int val) = 0;
+            /** @see setPolyN */
+            virtual int getPolyN() const = 0;
+            /** @copybrief getPolyN @see getPolyN */
+            virtual void setPolyN(int val) = 0;
+            /** @see setPolySigma */
+            virtual double getPolySigma() const = 0;
+            /** @copybrief getPolySigma @see getPolySigma */
+            virtual void setPolySigma(double val) = 0;
+            /** @see setFlags */
+            virtual int getFlags() const = 0;
+            /** @copybrief getFlags @see getFlags */
+            virtual void setFlags(int val) = 0;
+        };
+        CV_EXPORTS Ptr<FarnebackOpticalFlow> createOptFlow_Farneback();
+        CV_EXPORTS Ptr<FarnebackOpticalFlow> createOptFlow_Farneback_CUDA();
+
+
+//        CV_EXPORTS Ptr<DenseOpticalFlowExt> createOptFlow_Simple();
+
+
+        class CV_EXPORTS DualTVL1OpticalFlow : public virtual DenseOpticalFlowExt
+        {
+        public:
+            /** @see setTau */
+            virtual double getTau() const = 0;
+            /** @copybrief getTau @see getTau */
+            virtual void setTau(double val) = 0;
+            /** @see setLambda */
+            virtual double getLambda() const = 0;
+            /** @copybrief getLambda @see getLambda */
+            virtual void setLambda(double val) = 0;
+            /** @see setTheta */
+            virtual double getTheta() const = 0;
+            /** @copybrief getTheta @see getTheta */
+            virtual void setTheta(double val) = 0;
+            /** @see setScalesNumber */
+            virtual int getScalesNumber() const = 0;
+            /** @copybrief getScalesNumber @see getScalesNumber */
+            virtual void setScalesNumber(int val) = 0;
+            /** @see setWarpingsNumber */
+            virtual int getWarpingsNumber() const = 0;
+            /** @copybrief getWarpingsNumber @see getWarpingsNumber */
+            virtual void setWarpingsNumber(int val) = 0;
+            /** @see setEpsilon */
+            virtual double getEpsilon() const = 0;
+            /** @copybrief getEpsilon @see getEpsilon */
+            virtual void setEpsilon(double val) = 0;
+            /** @see setIterations */
+            virtual int getIterations() const = 0;
+            /** @copybrief getIterations @see getIterations */
+            virtual void setIterations(int val) = 0;
+            /** @see setUseInitialFlow */
+            virtual bool getUseInitialFlow() const = 0;
+            /** @copybrief getUseInitialFlow @see getUseInitialFlow */
+            virtual void setUseInitialFlow(bool val) = 0;
+        };
+        CV_EXPORTS Ptr<DualTVL1OpticalFlow> createOptFlow_DualTVL1();
+        CV_EXPORTS Ptr<DualTVL1OpticalFlow> createOptFlow_DualTVL1_CUDA();
+
+
+        class CV_EXPORTS BroxOpticalFlow : public virtual DenseOpticalFlowExt
+        {
+        public:
+            //! @brief Flow smoothness
+            /** @see setAlpha */
+            virtual double getAlpha() const = 0;
+            /** @copybrief getAlpha @see getAlpha */
+            virtual void setAlpha(double val) = 0;
+            //! @brief Gradient constancy importance
+            /** @see setGamma */
+            virtual double getGamma() const = 0;
+            /** @copybrief getGamma @see getGamma */
+            virtual void setGamma(double val) = 0;
+            //! @brief Pyramid scale factor
+            /** @see setScaleFactor */
+            virtual double getScaleFactor() const = 0;
+            /** @copybrief getScaleFactor @see getScaleFactor */
+            virtual void setScaleFactor(double val) = 0;
+            //! @brief Number of lagged non-linearity iterations (inner loop)
+            /** @see setInnerIterations */
+            virtual int getInnerIterations() const = 0;
+            /** @copybrief getInnerIterations @see getInnerIterations */
+            virtual void setInnerIterations(int val) = 0;
+            //! @brief Number of warping iterations (number of pyramid levels)
+            /** @see setOuterIterations */
+            virtual int getOuterIterations() const = 0;
+            /** @copybrief getOuterIterations @see getOuterIterations */
+            virtual void setOuterIterations(int val) = 0;
+            //! @brief Number of linear system solver iterations
+            /** @see setSolverIterations */
+            virtual int getSolverIterations() const = 0;
+            /** @copybrief getSolverIterations @see getSolverIterations */
+            virtual void setSolverIterations(int val) = 0;
+        };
+        CV_EXPORTS Ptr<BroxOpticalFlow> createOptFlow_Brox_CUDA();
+
+
+        class PyrLKOpticalFlow : public virtual DenseOpticalFlowExt
+        {
+        public:
+            /** @see setWindowSize */
+            virtual int getWindowSize() const = 0;
+            /** @copybrief getWindowSize @see getWindowSize */
+            virtual void setWindowSize(int val) = 0;
+            /** @see setMaxLevel */
+            virtual int getMaxLevel() const = 0;
+            /** @copybrief getMaxLevel @see getMaxLevel */
+            virtual void setMaxLevel(int val) = 0;
+            /** @see setIterations */
+            virtual int getIterations() const = 0;
+            /** @copybrief getIterations @see getIterations */
+            virtual void setIterations(int val) = 0;
+        };
+        CV_EXPORTS Ptr<PyrLKOpticalFlow> createOptFlow_PyrLK_CUDA();
+
+//! @}
+
+    }
+}
+
+#endif // OPENCV_SUPERRES_OPTICAL_FLOW_HPP

modules/superres/perf/perf_main.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "perf_precomp.hpp"
+
+using namespace perf;
+
+static const char * impls[] = {
+#ifdef HAVE_CUDA
+    "cuda",
+#endif
+    "plain"
+};
+
+#if defined(HAVE_HPX)
+    #include <hpx/hpx_main.hpp>
+#endif
+
+CV_PERF_TEST_MAIN_WITH_IMPLS(superres, impls, printCudaInfo())

modules/superres/perf/perf_precomp.hpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+#ifndef __OPENCV_PERF_PRECOMP_HPP__
+#define __OPENCV_PERF_PRECOMP_HPP__
+
+#include "opencv2/ts.hpp"
+#include "opencv2/core/cuda.hpp"
+#include "opencv2/ts/cuda_perf.hpp"
+#include "opencv2/superres.hpp"
+#include "opencv2/superres/optical_flow.hpp"
+
+#endif

modules/superres/perf/perf_superres.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "perf_precomp.hpp"
+#include "opencv2/ts/ocl_perf.hpp"
+
+namespace opencv_test
+{
+using namespace perf;
+using namespace cv::superres;
+using namespace cv::cuda;
+
+namespace
+{
+    class OneFrameSource_CPU : public FrameSource
+    {
+    public:
+        explicit OneFrameSource_CPU(const Mat& frame) : frame_(frame) {}
+
+        void nextFrame(OutputArray frame)
+        {
+            frame.getMatRef() = frame_;
+        }
+
+        void reset()
+        {
+        }
+
+    private:
+        Mat frame_;
+    };
+
+    class OneFrameSource_CUDA : public FrameSource
+    {
+    public:
+        explicit OneFrameSource_CUDA(const GpuMat& frame) : frame_(frame) {}
+
+        void nextFrame(OutputArray frame)
+        {
+            frame.getGpuMatRef() = frame_;
+        }
+
+        void reset()
+        {
+        }
+
+    private:
+        GpuMat frame_;
+    };
+
+    class ZeroOpticalFlow : public DenseOpticalFlowExt
+    {
+    public:
+        virtual void calc(InputArray frame0, InputArray, OutputArray flow1, OutputArray flow2)
+        {
+            cv::Size size = frame0.size();
+
+            if (!flow2.needed())
+            {
+                flow1.create(size, CV_32FC2);
+                flow1.setTo(cv::Scalar::all(0));
+            }
+            else
+            {
+                flow1.create(size, CV_32FC1);
+                flow2.create(size, CV_32FC1);
+
+                flow1.setTo(cv::Scalar::all(0));
+                flow2.setTo(cv::Scalar::all(0));
+            }
+        }
+
+        virtual void collectGarbage()
+        {
+        }
+    };
+} // namespace
+
+PERF_TEST_P(Size_MatType, SuperResolution_BTVL1,
+            Combine(Values(szSmall64, szSmall128),
+                    Values(MatType(CV_8UC1), MatType(CV_8UC3))))
+{
+    declare.time(5 * 60);
+
+    const Size size = get<0>(GetParam());
+    const int type = get<1>(GetParam());
+
+    Mat frame(size, type);
+    declare.in(frame, WARMUP_RNG);
+
+    const int scale = 2;
+    const int iterations = 50;
+    const int temporalAreaRadius = 1;
+    Ptr<DenseOpticalFlowExt> opticalFlow(new ZeroOpticalFlow);
+
+    if (PERF_RUN_CUDA())
+    {
+        Ptr<SuperResolution> superRes = createSuperResolution_BTVL1_CUDA();
+
+        superRes->setScale(scale);
+        superRes->setIterations(iterations);
+        superRes->setTemporalAreaRadius(temporalAreaRadius);
+        superRes->setOpticalFlow(opticalFlow);
+
+        superRes->setInput(makePtr<OneFrameSource_CUDA>(GpuMat(frame)));
+
+        GpuMat dst;
+        superRes->nextFrame(dst);
+
+        TEST_CYCLE_N(10) superRes->nextFrame(dst);
+
+        CUDA_SANITY_CHECK(dst, 2);
+    }
+    else
+    {
+        Ptr<SuperResolution> superRes = createSuperResolution_BTVL1();
+
+        superRes->setScale(scale);
+        superRes->setIterations(iterations);
+        superRes->setTemporalAreaRadius(temporalAreaRadius);
+        superRes->setOpticalFlow(opticalFlow);
+
+        superRes->setInput(makePtr<OneFrameSource_CPU>(frame));
+
+        Mat dst;
+        superRes->nextFrame(dst);
+
+        TEST_CYCLE_N(10) superRes->nextFrame(dst);
+
+        CPU_SANITY_CHECK(dst);
+    }
+}
+
+#ifdef HAVE_OPENCL
+
+namespace ocl {
+
+typedef Size_MatType SuperResolution_BTVL1;
+
+OCL_PERF_TEST_P(SuperResolution_BTVL1 ,BTVL1,
+            Combine(Values(szSmall64, szSmall128),
+                    Values(MatType(CV_8UC1), MatType(CV_8UC3))))
+{
+    Size_MatType_t params = GetParam();
+    const Size size = get<0>(params);
+    const int type = get<1>(params);
+
+    Mat frame(size, type);
+    UMat dst(1, 1, 0);
+    declare.in(frame, WARMUP_RNG);
+
+    const int scale = 2;
+    const int iterations = 50;
+    const int temporalAreaRadius = 1;
+
+    Ptr<DenseOpticalFlowExt> opticalFlow(new ZeroOpticalFlow);
+    Ptr<SuperResolution> superRes = createSuperResolution_BTVL1();
+
+    superRes->setScale(scale);
+    superRes->setIterations(iterations);
+    superRes->setTemporalAreaRadius(temporalAreaRadius);
+    superRes->setOpticalFlow(opticalFlow);
+
+    superRes->setInput(makePtr<OneFrameSource_CPU>(frame));
+
+    // skip first frame
+    superRes->nextFrame(dst);
+
+    OCL_TEST_CYCLE_N(10) superRes->nextFrame(dst);
+
+    SANITY_CHECK_NOTHING();
+}
+
+} // namespace ocl
+
+#endif // HAVE_OPENCL
+
+} // namespace

modules/superres/src/btv_l1.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+// S. Farsiu , D. Robinson, M. Elad, P. Milanfar. Fast and robust multiframe super resolution.
+// Dennis Mitzel, Thomas Pock, Thomas Schoenemann, Daniel Cremers. Video Super Resolution using Duality Based TV-L1 Optical Flow.
+
+#include "precomp.hpp"
+#include "opencl_kernels_superres.hpp"
+
+using namespace cv;
+using namespace cv::superres;
+using namespace cv::superres::detail;
+
+namespace
+{
+#ifdef HAVE_OPENCL
+
+    bool ocl_calcRelativeMotions(InputArrayOfArrays _forwardMotions, InputArrayOfArrays _backwardMotions,
+                                 OutputArrayOfArrays _relForwardMotions, OutputArrayOfArrays _relBackwardMotions,
+                                 int baseIdx, const Size & size)
+    {
+        std::vector<UMat> & forwardMotions = *(std::vector<UMat> *)_forwardMotions.getObj(),
+                & backwardMotions = *(std::vector<UMat> *)_backwardMotions.getObj(),
+                & relForwardMotions = *(std::vector<UMat> *)_relForwardMotions.getObj(),
+                & relBackwardMotions = *(std::vector<UMat> *)_relBackwardMotions.getObj();
+
+        const int count = static_cast<int>(forwardMotions.size());
+
+        relForwardMotions.resize(count);
+        relForwardMotions[baseIdx].create(size, CV_32FC2);
+        relForwardMotions[baseIdx].setTo(Scalar::all(0));
+
+        relBackwardMotions.resize(count);
+        relBackwardMotions[baseIdx].create(size, CV_32FC2);
+        relBackwardMotions[baseIdx].setTo(Scalar::all(0));
+
+        for (int i = baseIdx - 1; i >= 0; --i)
+        {
+            add(relForwardMotions[i + 1], forwardMotions[i], relForwardMotions[i]);
+            add(relBackwardMotions[i + 1], backwardMotions[i + 1], relBackwardMotions[i]);
+        }
+
+        for (int i = baseIdx + 1; i < count; ++i)
+        {
+            add(relForwardMotions[i - 1], backwardMotions[i], relForwardMotions[i]);
+            add(relBackwardMotions[i - 1], forwardMotions[i - 1], relBackwardMotions[i]);
+        }
+
+        return true;
+    }
+
+#endif
+
+    void calcRelativeMotions(InputArrayOfArrays _forwardMotions, InputArrayOfArrays _backwardMotions,
+                             OutputArrayOfArrays _relForwardMotions, OutputArrayOfArrays _relBackwardMotions,
+                             int baseIdx, const Size & size)
+    {
+        CV_OCL_RUN(_forwardMotions.isUMatVector() && _backwardMotions.isUMatVector() &&
+                   _relForwardMotions.isUMatVector() && _relBackwardMotions.isUMatVector(),
+                   ocl_calcRelativeMotions(_forwardMotions, _backwardMotions, _relForwardMotions,
+                                           _relBackwardMotions, baseIdx, size))
+
+        std::vector<Mat> & forwardMotions = *(std::vector<Mat> *)_forwardMotions.getObj(),
+                & backwardMotions = *(std::vector<Mat> *)_backwardMotions.getObj(),
+                & relForwardMotions = *(std::vector<Mat> *)_relForwardMotions.getObj(),
+                & relBackwardMotions = *(std::vector<Mat> *)_relBackwardMotions.getObj();
+
+        const int count = static_cast<int>(forwardMotions.size());
+
+        relForwardMotions.resize(count);
+        relForwardMotions[baseIdx].create(size, CV_32FC2);
+        relForwardMotions[baseIdx].setTo(Scalar::all(0));
+
+        relBackwardMotions.resize(count);
+        relBackwardMotions[baseIdx].create(size, CV_32FC2);
+        relBackwardMotions[baseIdx].setTo(Scalar::all(0));
+
+        for (int i = baseIdx - 1; i >= 0; --i)
+        {
+            add(relForwardMotions[i + 1], forwardMotions[i], relForwardMotions[i]);
+            add(relBackwardMotions[i + 1], backwardMotions[i + 1], relBackwardMotions[i]);
+        }
+
+        for (int i = baseIdx + 1; i < count; ++i)
+        {
+            add(relForwardMotions[i - 1], backwardMotions[i], relForwardMotions[i]);
+            add(relBackwardMotions[i - 1], forwardMotions[i - 1], relBackwardMotions[i]);
+        }
+    }
+#ifdef HAVE_OPENCL
+
+    bool ocl_upscaleMotions(InputArrayOfArrays _lowResMotions, OutputArrayOfArrays _highResMotions, int scale)
+    {
+        std::vector<UMat> & lowResMotions = *(std::vector<UMat> *)_lowResMotions.getObj(),
+                & highResMotions = *(std::vector<UMat> *)_highResMotions.getObj();
+
+        highResMotions.resize(lowResMotions.size());
+
+        for (size_t i = 0; i < lowResMotions.size(); ++i)
+        {
+            resize(lowResMotions[i], highResMotions[i], Size(), scale, scale, INTER_LINEAR); // TODO
+            multiply(highResMotions[i], Scalar::all(scale), highResMotions[i]);
+        }
+
+        return true;
+    }
+
+#endif
+
+    void upscaleMotions(InputArrayOfArrays _lowResMotions, OutputArrayOfArrays _highResMotions, int scale)
+    {
+        CV_OCL_RUN(_lowResMotions.isUMatVector() && _highResMotions.isUMatVector(),
+                   ocl_upscaleMotions(_lowResMotions, _highResMotions, scale))
+
+        std::vector<Mat> & lowResMotions = *(std::vector<Mat> *)_lowResMotions.getObj(),
+                & highResMotions = *(std::vector<Mat> *)_highResMotions.getObj();
+
+        highResMotions.resize(lowResMotions.size());
+
+        for (size_t i = 0; i < lowResMotions.size(); ++i)
+        {
+            resize(lowResMotions[i], highResMotions[i], Size(), scale, scale, INTER_CUBIC);
+            multiply(highResMotions[i], Scalar::all(scale), highResMotions[i]);
+        }
+    }
+
+#ifdef HAVE_OPENCL
+
+    bool ocl_buildMotionMaps(InputArray _forwardMotion, InputArray _backwardMotion,
+                             OutputArray _forwardMap, OutputArray _backwardMap)
+    {
+        ocl::Kernel k("buildMotionMaps", ocl::superres::superres_btvl1_oclsrc);
+        if (k.empty())
+            return false;
+
+        UMat forwardMotion = _forwardMotion.getUMat(), backwardMotion = _backwardMotion.getUMat();
+        Size size = forwardMotion.size();
+
+        _forwardMap.create(size, CV_32FC2);
+        _backwardMap.create(size, CV_32FC2);
+
+        UMat forwardMap = _forwardMap.getUMat(), backwardMap = _backwardMap.getUMat();
+
+        k.args(ocl::KernelArg::ReadOnlyNoSize(forwardMotion),
+               ocl::KernelArg::ReadOnlyNoSize(backwardMotion),
+               ocl::KernelArg::WriteOnlyNoSize(forwardMap),
+               ocl::KernelArg::WriteOnly(backwardMap));
+
+        size_t globalsize[2] = { (size_t)size.width, (size_t)size.height };
+        return k.run(2, globalsize, NULL, false);
+    }
+
+#endif
+
+    void buildMotionMaps(InputArray _forwardMotion, InputArray _backwardMotion,
+                         OutputArray _forwardMap, OutputArray _backwardMap)
+    {
+        CV_OCL_RUN(_forwardMap.isUMat() && _backwardMap.isUMat(),
+                   ocl_buildMotionMaps(_forwardMotion, _backwardMotion, _forwardMap,
+                                       _backwardMap));
+
+        Mat forwardMotion = _forwardMotion.getMat(), backwardMotion = _backwardMotion.getMat();
+
+        _forwardMap.create(forwardMotion.size(), CV_32FC2);
+        _backwardMap.create(forwardMotion.size(), CV_32FC2);
+
+        Mat forwardMap = _forwardMap.getMat(), backwardMap = _backwardMap.getMat();
+
+        for (int y = 0; y < forwardMotion.rows; ++y)
+        {
+            const Point2f* forwardMotionRow = forwardMotion.ptr<Point2f>(y);
+            const Point2f* backwardMotionRow = backwardMotion.ptr<Point2f>(y);
+            Point2f* forwardMapRow = forwardMap.ptr<Point2f>(y);
+            Point2f* backwardMapRow = backwardMap.ptr<Point2f>(y);
+
+            for (int x = 0; x < forwardMotion.cols; ++x)
+            {
+                Point2f base(static_cast<float>(x), static_cast<float>(y));
+
+                forwardMapRow[x] = base + backwardMotionRow[x];
+                backwardMapRow[x] = base + forwardMotionRow[x];
+            }
+        }
+    }
+
+    template <typename T>
+    void upscaleImpl(InputArray _src, OutputArray _dst, int scale)
+    {
+        Mat src = _src.getMat();
+        _dst.create(src.rows * scale, src.cols * scale, src.type());
+        _dst.setTo(Scalar::all(0));
+        Mat dst = _dst.getMat();
+
+        for (int y = 0, Y = 0; y < src.rows; ++y, Y += scale)
+        {
+            const T * const srcRow = src.ptr<T>(y);
+            T * const dstRow = dst.ptr<T>(Y);
+
+            for (int x = 0, X = 0; x < src.cols; ++x, X += scale)
+                dstRow[X] = srcRow[x];
+        }
+    }
+
+#ifdef HAVE_OPENCL
+
+    static bool ocl_upscale(InputArray _src, OutputArray _dst, int scale)
+    {
+        int type = _src.type(), cn = CV_MAT_CN(type);
+        ocl::Kernel k("upscale", ocl::superres::superres_btvl1_oclsrc,
+                      format("-D cn=%d", cn));
+        if (k.empty())
+            return false;
+
+        UMat src = _src.getUMat();
+        _dst.create(src.rows * scale, src.cols * scale, type);
+        _dst.setTo(Scalar::all(0));
+        UMat dst = _dst.getUMat();
+
+        k.args(ocl::KernelArg::ReadOnly(src),
+               ocl::KernelArg::ReadWriteNoSize(dst), scale);
+
+        size_t globalsize[2] = { (size_t)src.cols, (size_t)src.rows };
+        return k.run(2, globalsize, NULL, false);
+    }
+
+#endif
+
+    typedef struct _Point4f { float ar[4]; } Point4f;
+
+    void upscale(InputArray _src, OutputArray _dst, int scale)
+    {
+        int cn = _src.channels();
+        CV_Assert( cn == 1 || cn == 3 || cn == 4 );
+
+        CV_OCL_RUN(_dst.isUMat(),
+                   ocl_upscale(_src, _dst, scale))
+
+        typedef void (*func_t)(InputArray src, OutputArray dst, int scale);
+        static const func_t funcs[] =
+        {
+            0, upscaleImpl<float>, 0, upscaleImpl<Point3f>, upscaleImpl<Point4f>
+        };
+
+        const func_t func = funcs[cn];
+        CV_Assert(func != 0);
+        func(_src, _dst, scale);
+    }
+
+    inline float diffSign(float a, float b)
+    {
+        return a > b ? 1.0f : a < b ? -1.0f : 0.0f;
+    }
+
+    Point3f diffSign(Point3f a, Point3f b)
+    {
+        return Point3f(
+            a.x > b.x ? 1.0f : a.x < b.x ? -1.0f : 0.0f,
+            a.y > b.y ? 1.0f : a.y < b.y ? -1.0f : 0.0f,
+            a.z > b.z ? 1.0f : a.z < b.z ? -1.0f : 0.0f
+        );
+    }
+
+#ifdef HAVE_OPENCL
+
+    static bool ocl_diffSign(InputArray _src1, OutputArray _src2, OutputArray _dst)
+    {
+        ocl::Kernel k("diffSign", ocl::superres::superres_btvl1_oclsrc);
+        if (k.empty())
+            return false;
+
+        UMat src1 = _src1.getUMat(), src2 = _src2.getUMat();
+        _dst.create(src1.size(), src1.type());
+        UMat dst = _dst.getUMat();
+
+        int cn = src1.channels();
+        k.args(ocl::KernelArg::ReadOnlyNoSize(src1),
+               ocl::KernelArg::ReadOnlyNoSize(src2),
+               ocl::KernelArg::WriteOnly(dst, cn));
+
+        size_t globalsize[2] = { (size_t)src1.cols * cn, (size_t)src1.rows };
+        return k.run(2, globalsize, NULL, false);
+    }
+
+#endif
+
+    void diffSign(InputArray _src1, OutputArray _src2, OutputArray _dst)
+    {
+        CV_OCL_RUN(_dst.isUMat(),
+                   ocl_diffSign(_src1, _src2, _dst))
+
+        Mat src1 = _src1.getMat(), src2 = _src2.getMat();
+        _dst.create(src1.size(), src1.type());
+        Mat dst = _dst.getMat();
+
+        const int count = src1.cols * src1.channels();
+
+        for (int y = 0; y < src1.rows; ++y)
+        {
+            const float * const src1Ptr = src1.ptr<float>(y);
+            const float * const src2Ptr = src2.ptr<float>(y);
+            float* dstPtr = dst.ptr<float>(y);
+
+            for (int x = 0; x < count; ++x)
+                dstPtr[x] = diffSign(src1Ptr[x], src2Ptr[x]);
+        }
+    }
+
+    void calcBtvWeights(int btvKernelSize, double alpha, std::vector<float>& btvWeights)
+    {
+        const size_t size = btvKernelSize * btvKernelSize;
+
+        btvWeights.resize(size);
+
+        const int ksize = (btvKernelSize - 1) / 2;
+        const float alpha_f = static_cast<float>(alpha);
+
+        for (int m = 0, ind = 0; m <= ksize; ++m)
+        {
+            for (int l = ksize; l + m >= 0; --l, ++ind)
+                btvWeights[ind] = pow(alpha_f, std::abs(m) + std::abs(l));
+        }
+    }
+
+    template <typename T>
+    struct BtvRegularizationBody : ParallelLoopBody
+    {
+        void operator ()(const Range& range) const CV_OVERRIDE;
+
+        Mat src;
+        mutable Mat dst;
+        int ksize;
+        const float* btvWeights;
+    };
+
+    template <typename T>
+    void BtvRegularizationBody<T>::operator ()(const Range& range) const
+    {
+        for (int i = range.start; i < range.end; ++i)
+        {
+            const T * const srcRow = src.ptr<T>(i);
+            T * const dstRow = dst.ptr<T>(i);
+
+            for(int j = ksize; j < src.cols - ksize; ++j)
+            {
+                const T srcVal = srcRow[j];
+
+                for (int m = 0, ind = 0; m <= ksize; ++m)
+                {
+                    const T* srcRow2 = src.ptr<T>(i - m);
+                    const T* srcRow3 = src.ptr<T>(i + m);
+
+                    for (int l = ksize; l + m >= 0; --l, ++ind)
+                        dstRow[j] += btvWeights[ind] * (diffSign(srcVal, srcRow3[j + l])
+                                                        - diffSign(srcRow2[j - l], srcVal));
+                }
+            }
+        }
+    }
+
+    template <typename T>
+    void calcBtvRegularizationImpl(InputArray _src, OutputArray _dst, int btvKernelSize, const std::vector<float>& btvWeights)
+    {
+        Mat src = _src.getMat();
+        _dst.create(src.size(), src.type());
+        _dst.setTo(Scalar::all(0));
+        Mat dst = _dst.getMat();
+
+        const int ksize = (btvKernelSize - 1) / 2;
+
+        BtvRegularizationBody<T> body;
+
+        body.src = src;
+        body.dst = dst;
+        body.ksize = ksize;
+        body.btvWeights = &btvWeights[0];
+
+        parallel_for_(Range(ksize, src.rows - ksize), body);
+    }
+
+#ifdef HAVE_OPENCL
+
+    static bool ocl_calcBtvRegularization(InputArray _src, OutputArray _dst, int btvKernelSize, const UMat & ubtvWeights)
+    {
+        int cn = _src.channels();
+        ocl::Kernel k("calcBtvRegularization", ocl::superres::superres_btvl1_oclsrc,
+                      format("-D cn=%d", cn));
+        if (k.empty())
+            return false;
+
+        UMat src = _src.getUMat();
+        _dst.create(src.size(), src.type());
+        _dst.setTo(Scalar::all(0));
+        UMat dst = _dst.getUMat();
+
+        const int ksize = (btvKernelSize - 1) / 2;
+
+        k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst),
+              ksize, ocl::KernelArg::PtrReadOnly(ubtvWeights));
+
+        size_t globalsize[2] = { (size_t)src.cols, (size_t)src.rows };
+        return k.run(2, globalsize, NULL, false);
+    }
+
+#endif
+
+    void calcBtvRegularization(InputArray _src, OutputArray _dst, int btvKernelSize,
+                               const std::vector<float>& btvWeights, const UMat & ubtvWeights)
+    {
+        CV_OCL_RUN(_dst.isUMat(),
+                   ocl_calcBtvRegularization(_src, _dst, btvKernelSize, ubtvWeights))
+        CV_UNUSED(ubtvWeights);
+        if (_src.channels() == 1)
+        {
+            calcBtvRegularizationImpl<float>(_src, _dst, btvKernelSize, btvWeights);
+        }
+        else if (_src.channels() == 3)
+        {
+            calcBtvRegularizationImpl<Point3f>(_src, _dst, btvKernelSize, btvWeights);
+        }
+        else
+        {
+            CV_Error(Error::StsBadArg, "Unsupported number of channels in _src");
+        }
+    }
+
+    class BTVL1_Base : public cv::superres::SuperResolution
+    {
+    public:
+        BTVL1_Base();
+
+        void process(InputArrayOfArrays src, OutputArray dst, InputArrayOfArrays forwardMotions,
+                     InputArrayOfArrays backwardMotions, int baseIdx);
+
+        void collectGarbage() CV_OVERRIDE;
+
+        inline int getScale() const CV_OVERRIDE { return scale_; }
+        inline void setScale(int val) CV_OVERRIDE { scale_ = val; }
+        inline int getIterations() const CV_OVERRIDE { return iterations_; }
+        inline void setIterations(int val) CV_OVERRIDE { iterations_ = val; }
+        inline double getTau() const CV_OVERRIDE { return tau_; }
+        inline void setTau(double val) CV_OVERRIDE { tau_ = val; }
+        inline double getLabmda() const CV_OVERRIDE { return lambda_; }
+        inline void setLabmda(double val) CV_OVERRIDE { lambda_ = val; }
+        inline double getAlpha() const CV_OVERRIDE { return alpha_; }
+        inline void setAlpha(double val) CV_OVERRIDE { alpha_ = val; }
+        inline int getKernelSize() const CV_OVERRIDE { return btvKernelSize_; }
+        inline void setKernelSize(int val) CV_OVERRIDE { btvKernelSize_ = val; }
+        inline int getBlurKernelSize() const CV_OVERRIDE { return blurKernelSize_; }
+        inline void setBlurKernelSize(int val) CV_OVERRIDE { blurKernelSize_ = val; }
+        inline double getBlurSigma() const CV_OVERRIDE { return blurSigma_; }
+        inline void setBlurSigma(double val) CV_OVERRIDE { blurSigma_ = val; }
+        inline int getTemporalAreaRadius() const CV_OVERRIDE { return temporalAreaRadius_; }
+        inline void setTemporalAreaRadius(int val) CV_OVERRIDE { temporalAreaRadius_ = val; }
+        inline Ptr<cv::superres::DenseOpticalFlowExt> getOpticalFlow() const CV_OVERRIDE { return opticalFlow_; }
+        inline void setOpticalFlow(const Ptr<cv::superres::DenseOpticalFlowExt>& val) CV_OVERRIDE { opticalFlow_ = val; }
+
+    protected:
+        int scale_;
+        int iterations_;
+        double tau_;
+        double lambda_;
+        double alpha_;
+        int btvKernelSize_;
+        int blurKernelSize_;
+        double blurSigma_;
+        int temporalAreaRadius_; // not used in some implementations
+        Ptr<cv::superres::DenseOpticalFlowExt> opticalFlow_;
+
+    private:
+        bool ocl_process(InputArrayOfArrays src, OutputArray dst, InputArrayOfArrays forwardMotions,
+                         InputArrayOfArrays backwardMotions, int baseIdx);
+
+        //Ptr<FilterEngine> filter_;
+        int curBlurKernelSize_;
+        double curBlurSigma_;
+        int curSrcType_;
+
+        std::vector<float> btvWeights_;
+        UMat ubtvWeights_;
+
+        int curBtvKernelSize_;
+        double curAlpha_;
+
+        // Mat
+        std::vector<Mat> lowResForwardMotions_;
+        std::vector<Mat> lowResBackwardMotions_;
+
+        std::vector<Mat> highResForwardMotions_;
+        std::vector<Mat> highResBackwardMotions_;
+
+        std::vector<Mat> forwardMaps_;
+        std::vector<Mat> backwardMaps_;
+
+        Mat highRes_;
+
+        Mat diffTerm_, regTerm_;
+        Mat a_, b_, c_;
+
+#ifdef HAVE_OPENCL
+        // UMat
+        std::vector<UMat> ulowResForwardMotions_;
+        std::vector<UMat> ulowResBackwardMotions_;
+
+        std::vector<UMat> uhighResForwardMotions_;
+        std::vector<UMat> uhighResBackwardMotions_;
+
+        std::vector<UMat> uforwardMaps_;
+        std::vector<UMat> ubackwardMaps_;
+
+        UMat uhighRes_;
+
+        UMat udiffTerm_, uregTerm_;
+        UMat ua_, ub_, uc_;
+#endif
+    };
+
+    BTVL1_Base::BTVL1_Base()
+    {
+        scale_ = 4;
+        iterations_ = 180;
+        lambda_ = 0.03;
+        tau_ = 1.3;
+        alpha_ = 0.7;
+        btvKernelSize_ = 7;
+        blurKernelSize_ = 5;
+        blurSigma_ = 0.0;
+        temporalAreaRadius_ = 0;
+        opticalFlow_ = createOptFlow_Farneback();
+
+        curBlurKernelSize_ = -1;
+        curBlurSigma_ = -1.0;
+        curSrcType_ = -1;
+
+        curBtvKernelSize_ = -1;
+        curAlpha_ = -1.0;
+    }
+
+#ifdef HAVE_OPENCL
+
+    bool BTVL1_Base::ocl_process(InputArrayOfArrays _src, OutputArray _dst, InputArrayOfArrays _forwardMotions,
+                                 InputArrayOfArrays _backwardMotions, int baseIdx)
+    {
+        std::vector<UMat> & src = *(std::vector<UMat> *)_src.getObj(),
+                & forwardMotions = *(std::vector<UMat> *)_forwardMotions.getObj(),
+                & backwardMotions = *(std::vector<UMat> *)_backwardMotions.getObj();
+
+        // update blur filter and btv weights
+        if (blurKernelSize_ != curBlurKernelSize_ || blurSigma_ != curBlurSigma_ || src[0].type() != curSrcType_)
+        {
+            //filter_ = createGaussianFilter(src[0].type(), Size(blurKernelSize_, blurKernelSize_), blurSigma_);
+            curBlurKernelSize_ = blurKernelSize_;
+            curBlurSigma_ = blurSigma_;
+            curSrcType_ = src[0].type();
+        }
+
+        if (btvWeights_.empty() || btvKernelSize_ != curBtvKernelSize_ || alpha_ != curAlpha_)
+        {
+            calcBtvWeights(btvKernelSize_, alpha_, btvWeights_);
+            Mat(btvWeights_, true).copyTo(ubtvWeights_);
+
+            curBtvKernelSize_ = btvKernelSize_;
+            curAlpha_ = alpha_;
+        }
+
+        // calc high res motions
+        calcRelativeMotions(forwardMotions, backwardMotions, ulowResForwardMotions_, ulowResBackwardMotions_, baseIdx, src[0].size());
+
+        upscaleMotions(ulowResForwardMotions_, uhighResForwardMotions_, scale_);
+        upscaleMotions(ulowResBackwardMotions_, uhighResBackwardMotions_, scale_);
+
+        uforwardMaps_.resize(uhighResForwardMotions_.size());
+        ubackwardMaps_.resize(uhighResForwardMotions_.size());
+        for (size_t i = 0; i < uhighResForwardMotions_.size(); ++i)
+            buildMotionMaps(uhighResForwardMotions_[i], uhighResBackwardMotions_[i], uforwardMaps_[i], ubackwardMaps_[i]);
+
+        // initial estimation
+        const Size lowResSize = src[0].size();
+        const Size highResSize(lowResSize.width * scale_, lowResSize.height * scale_);
+
+        resize(src[baseIdx], uhighRes_, highResSize, 0, 0, INTER_LINEAR); // TODO
+
+        // iterations
+        udiffTerm_.create(highResSize, uhighRes_.type());
+        ua_.create(highResSize, uhighRes_.type());
+        ub_.create(highResSize, uhighRes_.type());
+        uc_.create(lowResSize, uhighRes_.type());
+
+        for (int i = 0; i < iterations_; ++i)
+        {
+            udiffTerm_.setTo(Scalar::all(0));
+
+            for (size_t k = 0; k < src.size(); ++k)
+            {
+                // a = M * Ih
+                remap(uhighRes_, ua_, ubackwardMaps_[k], noArray(), INTER_NEAREST);
+                // b = HM * Ih
+                GaussianBlur(ua_, ub_, Size(blurKernelSize_, blurKernelSize_), blurSigma_);
+                // c = DHM * Ih
+                resize(ub_, uc_, lowResSize, 0, 0, INTER_NEAREST);
+
+                diffSign(src[k], uc_, uc_);
+
+                // a = Dt * diff
+                upscale(uc_, ua_, scale_);
+
+                // b = HtDt * diff
+                GaussianBlur(ua_, ub_, Size(blurKernelSize_, blurKernelSize_), blurSigma_);
+                // a = MtHtDt * diff
+                remap(ub_, ua_, uforwardMaps_[k], noArray(), INTER_NEAREST);
+
+                add(udiffTerm_, ua_, udiffTerm_);
+            }
+
+            if (lambda_ > 0)
+            {
+                calcBtvRegularization(uhighRes_, uregTerm_, btvKernelSize_, btvWeights_, ubtvWeights_);
+                addWeighted(udiffTerm_, 1.0, uregTerm_, -lambda_, 0.0, udiffTerm_);
+            }
+
+            addWeighted(uhighRes_, 1.0, udiffTerm_, tau_, 0.0, uhighRes_);
+        }
+
+        Rect inner(btvKernelSize_, btvKernelSize_, uhighRes_.cols - 2 * btvKernelSize_, uhighRes_.rows - 2 * btvKernelSize_);
+        uhighRes_(inner).copyTo(_dst);
+
+        return true;
+    }
+
+#endif
+
+    void BTVL1_Base::process(InputArrayOfArrays _src, OutputArray _dst, InputArrayOfArrays _forwardMotions,
+                             InputArrayOfArrays _backwardMotions, int baseIdx)
+    {
+        CV_INSTRUMENT_REGION();
+
+        CV_Assert( scale_ > 1 );
+        CV_Assert( iterations_ > 0 );
+        CV_Assert( tau_ > 0.0 );
+        CV_Assert( alpha_ > 0.0 );
+        CV_Assert( btvKernelSize_ > 0 );
+        CV_Assert( blurKernelSize_ > 0 );
+        CV_Assert( blurSigma_ >= 0.0 );
+
+        CV_OCL_RUN(_src.isUMatVector() && _dst.isUMat() && _forwardMotions.isUMatVector() &&
+                   _backwardMotions.isUMatVector(),
+                   ocl_process(_src, _dst, _forwardMotions, _backwardMotions, baseIdx))
+
+        std::vector<Mat> & src = *(std::vector<Mat> *)_src.getObj(),
+                & forwardMotions = *(std::vector<Mat> *)_forwardMotions.getObj(),
+                & backwardMotions = *(std::vector<Mat> *)_backwardMotions.getObj();
+
+        // update blur filter and btv weights
+        if (blurKernelSize_ != curBlurKernelSize_ || blurSigma_ != curBlurSigma_ || src[0].type() != curSrcType_)
+        {
+            //filter_ = createGaussianFilter(src[0].type(), Size(blurKernelSize_, blurKernelSize_), blurSigma_);
+            curBlurKernelSize_ = blurKernelSize_;
+            curBlurSigma_ = blurSigma_;
+            curSrcType_ = src[0].type();
+        }
+
+        if (btvWeights_.empty() || btvKernelSize_ != curBtvKernelSize_ || alpha_ != curAlpha_)
+        {
+            calcBtvWeights(btvKernelSize_, alpha_, btvWeights_);
+            curBtvKernelSize_ = btvKernelSize_;
+            curAlpha_ = alpha_;
+        }
+
+        // calc high res motions
+        calcRelativeMotions(forwardMotions, backwardMotions, lowResForwardMotions_, lowResBackwardMotions_, baseIdx, src[0].size());
+
+        upscaleMotions(lowResForwardMotions_, highResForwardMotions_, scale_);
+        upscaleMotions(lowResBackwardMotions_, highResBackwardMotions_, scale_);
+
+        forwardMaps_.resize(highResForwardMotions_.size());
+        backwardMaps_.resize(highResForwardMotions_.size());
+        for (size_t i = 0; i < highResForwardMotions_.size(); ++i)
+            buildMotionMaps(highResForwardMotions_[i], highResBackwardMotions_[i], forwardMaps_[i], backwardMaps_[i]);
+
+        // initial estimation
+        const Size lowResSize = src[0].size();
+        const Size highResSize(lowResSize.width * scale_, lowResSize.height * scale_);
+
+        resize(src[baseIdx], highRes_, highResSize, 0, 0, INTER_CUBIC);
+
+        // iterations
+        diffTerm_.create(highResSize, highRes_.type());
+        a_.create(highResSize, highRes_.type());
+        b_.create(highResSize, highRes_.type());
+        c_.create(lowResSize, highRes_.type());
+
+        for (int i = 0; i < iterations_; ++i)
+        {
+            diffTerm_.setTo(Scalar::all(0));
+
+            for (size_t k = 0; k < src.size(); ++k)
+            {
+                // a = M * Ih
+                remap(highRes_, a_, backwardMaps_[k], noArray(), INTER_NEAREST);
+                // b = HM * Ih
+                GaussianBlur(a_, b_, Size(blurKernelSize_, blurKernelSize_), blurSigma_);
+                // c = DHM * Ih
+                resize(b_, c_, lowResSize, 0, 0, INTER_NEAREST);
+
+                diffSign(src[k], c_, c_);
+
+                // a = Dt * diff
+                upscale(c_, a_, scale_);
+                // b = HtDt * diff
+                GaussianBlur(a_, b_, Size(blurKernelSize_, blurKernelSize_), blurSigma_);
+                // a = MtHtDt * diff
+                remap(b_, a_, forwardMaps_[k], noArray(), INTER_NEAREST);
+
+                add(diffTerm_, a_, diffTerm_);
+            }
+
+            if (lambda_ > 0)
+            {
+                calcBtvRegularization(highRes_, regTerm_, btvKernelSize_, btvWeights_, ubtvWeights_);
+                addWeighted(diffTerm_, 1.0, regTerm_, -lambda_, 0.0, diffTerm_);
+            }
+
+            addWeighted(highRes_, 1.0, diffTerm_, tau_, 0.0, highRes_);
+        }
+
+        Rect inner(btvKernelSize_, btvKernelSize_, highRes_.cols - 2 * btvKernelSize_, highRes_.rows - 2 * btvKernelSize_);
+        highRes_(inner).copyTo(_dst);
+    }
+
+    void BTVL1_Base::collectGarbage()
+    {
+        // Mat
+        lowResForwardMotions_.clear();
+        lowResBackwardMotions_.clear();
+
+        highResForwardMotions_.clear();
+        highResBackwardMotions_.clear();
+
+        forwardMaps_.clear();
+        backwardMaps_.clear();
+
+        highRes_.release();
+
+        diffTerm_.release();
+        regTerm_.release();
+        a_.release();
+        b_.release();
+        c_.release();
+
+#ifdef HAVE_OPENCL
+        // UMat
+        ulowResForwardMotions_.clear();
+        ulowResBackwardMotions_.clear();
+
+        uhighResForwardMotions_.clear();
+        uhighResBackwardMotions_.clear();
+
+        uforwardMaps_.clear();
+        ubackwardMaps_.clear();
+
+        uhighRes_.release();
+
+        udiffTerm_.release();
+        uregTerm_.release();
+        ua_.release();
+        ub_.release();
+        uc_.release();
+#endif
+    }
+
+////////////////////////////////////////////////////////////////////
+
+    class BTVL1 CV_FINAL : public BTVL1_Base
+    {
+    public:
+        BTVL1();
+
+        void collectGarbage() CV_OVERRIDE;
+
+    protected:
+        void initImpl(Ptr<FrameSource>& frameSource) CV_OVERRIDE;
+        bool ocl_initImpl(Ptr<FrameSource>& frameSource);
+
+        void processImpl(Ptr<FrameSource>& frameSource, OutputArray output) CV_OVERRIDE;
+        bool ocl_processImpl(Ptr<FrameSource>& frameSource, OutputArray output);
+
+    private:
+        void readNextFrame(Ptr<FrameSource>& frameSource);
+        bool ocl_readNextFrame(Ptr<FrameSource>& frameSource);
+
+        void processFrame(int idx);
+        bool ocl_processFrame(int idx);
+
+        int storePos_;
+        int procPos_;
+        int outPos_;
+
+        // Mat
+        Mat curFrame_;
+        Mat prevFrame_;
+
+        std::vector<Mat> frames_;
+        std::vector<Mat> forwardMotions_;
+        std::vector<Mat> backwardMotions_;
+        std::vector<Mat> outputs_;
+
+        std::vector<Mat> srcFrames_;
+        std::vector<Mat> srcForwardMotions_;
+        std::vector<Mat> srcBackwardMotions_;
+        Mat finalOutput_;
+
+#ifdef HAVE_OPENCL
+        // UMat
+        UMat ucurFrame_;
+        UMat uprevFrame_;
+
+        std::vector<UMat> uframes_;
+        std::vector<UMat> uforwardMotions_;
+        std::vector<UMat> ubackwardMotions_;
+        std::vector<UMat> uoutputs_;
+
+        std::vector<UMat> usrcFrames_;
+        std::vector<UMat> usrcForwardMotions_;
+        std::vector<UMat> usrcBackwardMotions_;
+#endif
+    };
+
+    BTVL1::BTVL1()
+    {
+        temporalAreaRadius_ = 4;
+        procPos_ = 0;
+        outPos_ = 0;
+        storePos_ = 0;
+    }
+
+    void BTVL1::collectGarbage()
+    {
+        // Mat
+        curFrame_.release();
+        prevFrame_.release();
+
+        frames_.clear();
+        forwardMotions_.clear();
+        backwardMotions_.clear();
+        outputs_.clear();
+
+        srcFrames_.clear();
+        srcForwardMotions_.clear();
+        srcBackwardMotions_.clear();
+        finalOutput_.release();
+
+#ifdef HAVE_OPENCL
+        // UMat
+        ucurFrame_.release();
+        uprevFrame_.release();
+
+        uframes_.clear();
+        uforwardMotions_.clear();
+        ubackwardMotions_.clear();
+        uoutputs_.clear();
+
+        usrcFrames_.clear();
+        usrcForwardMotions_.clear();
+        usrcBackwardMotions_.clear();
+#endif
+
+        SuperResolution::collectGarbage();
+        BTVL1_Base::collectGarbage();
+    }
+
+#ifdef HAVE_OPENCL
+
+    bool BTVL1::ocl_initImpl(Ptr<FrameSource>& frameSource)
+    {
+        const int cacheSize = 2 * temporalAreaRadius_ + 1;
+
+        uframes_.resize(cacheSize);
+        uforwardMotions_.resize(cacheSize);
+        ubackwardMotions_.resize(cacheSize);
+        uoutputs_.resize(cacheSize);
+
+        storePos_ = -1;
+
+        for (int t = -temporalAreaRadius_; t <= temporalAreaRadius_; ++t)
+            readNextFrame(frameSource);
+
+        for (int i = 0; i <= temporalAreaRadius_; ++i)
+            processFrame(i);
+
+        procPos_ = temporalAreaRadius_;
+        outPos_ = -1;
+
+        return true;
+    }
+
+#endif
+
+    void BTVL1::initImpl(Ptr<FrameSource>& frameSource)
+    {
+        const int cacheSize = 2 * temporalAreaRadius_ + 1;
+
+        frames_.resize(cacheSize);
+        forwardMotions_.resize(cacheSize);
+        backwardMotions_.resize(cacheSize);
+        outputs_.resize(cacheSize);
+
+        CV_OCL_RUN(isUmat_,
+                   ocl_initImpl(frameSource))
+
+        storePos_ = -1;
+
+        for (int t = -temporalAreaRadius_; t <= temporalAreaRadius_; ++t)
+            readNextFrame(frameSource);
+
+        for (int i = 0; i <= temporalAreaRadius_; ++i)
+            processFrame(i);
+
+        procPos_ = temporalAreaRadius_;
+        outPos_ = -1;
+    }
+
+#ifdef HAVE_OPENCL
+
+    bool BTVL1::ocl_processImpl(Ptr<FrameSource>& /*frameSource*/, OutputArray _output)
+    {
+        const UMat& curOutput = at(outPos_, uoutputs_);
+        curOutput.convertTo(_output, CV_8U);
+
+        return true;
+    }
+
+#endif
+
+    void BTVL1::processImpl(Ptr<FrameSource>& frameSource, OutputArray _output)
+    {
+        CV_INSTRUMENT_REGION();
+
+        if (outPos_ >= storePos_)
+        {
+            _output.release();
+            return;
+        }
+
+        readNextFrame(frameSource);
+
+        if (procPos_ < storePos_)
+        {
+            ++procPos_;
+            processFrame(procPos_);
+        }
+        ++outPos_;
+
+        CV_OCL_RUN(isUmat_,
+                   ocl_processImpl(frameSource, _output))
+
+        const Mat& curOutput = at(outPos_, outputs_);
+
+        if (_output.kind() < _InputArray::OPENGL_BUFFER || _output.isUMat())
+            curOutput.convertTo(_output, CV_8U);
+        else
+        {
+            curOutput.convertTo(finalOutput_, CV_8U);
+            arrCopy(finalOutput_, _output);
+        }
+    }
+
+#ifdef HAVE_OPENCL
+
+    bool BTVL1::ocl_readNextFrame(Ptr<FrameSource>& /*frameSource*/)
+    {
+        ucurFrame_.convertTo(at(storePos_, uframes_), CV_32F);
+
+        if (storePos_ > 0)
+        {
+            opticalFlow_->calc(uprevFrame_, ucurFrame_, at(storePos_ - 1, uforwardMotions_));
+            opticalFlow_->calc(ucurFrame_, uprevFrame_, at(storePos_, ubackwardMotions_));
+        }
+
+        ucurFrame_.copyTo(uprevFrame_);
+        return true;
+    }
+
+#endif
+
+    void BTVL1::readNextFrame(Ptr<FrameSource>& frameSource)
+    {
+        CV_INSTRUMENT_REGION();
+
+        frameSource->nextFrame(curFrame_);
+        if (curFrame_.empty())
+            return;
+
+#ifdef HAVE_OPENCL
+        if (isUmat_)
+            curFrame_.copyTo(ucurFrame_);
+#endif
+        ++storePos_;
+
+        CV_OCL_RUN(isUmat_,
+                   ocl_readNextFrame(frameSource))
+
+        curFrame_.convertTo(at(storePos_, frames_), CV_32F);
+
+        if (storePos_ > 0)
+        {
+            opticalFlow_->calc(prevFrame_, curFrame_, at(storePos_ - 1, forwardMotions_));
+            opticalFlow_->calc(curFrame_, prevFrame_, at(storePos_, backwardMotions_));
+        }
+
+        curFrame_.copyTo(prevFrame_);
+    }
+
+#ifdef HAVE_OPENCL
+
+    bool BTVL1::ocl_processFrame(int idx)
+    {
+        const int startIdx = std::max(idx - temporalAreaRadius_, 0);
+        const int procIdx = idx;
+        const int endIdx = std::min(startIdx + 2 * temporalAreaRadius_, storePos_);
+
+        const int count = endIdx - startIdx + 1;
+
+        usrcFrames_.resize(count);
+        usrcForwardMotions_.resize(count);
+        usrcBackwardMotions_.resize(count);
+
+        int baseIdx = -1;
+
+        for (int i = startIdx, k = 0; i <= endIdx; ++i, ++k)
+        {
+            if (i == procIdx)
+                baseIdx = k;
+
+            usrcFrames_[k] = at(i, uframes_);
+
+            if (i < endIdx)
+                usrcForwardMotions_[k] = at(i, uforwardMotions_);
+            if (i > startIdx)
+                usrcBackwardMotions_[k] = at(i, ubackwardMotions_);
+        }
+
+        process(usrcFrames_, at(idx, uoutputs_), usrcForwardMotions_, usrcBackwardMotions_, baseIdx);
+
+        return true;
+    }
+
+#endif
+
+    void BTVL1::processFrame(int idx)
+    {
+        CV_INSTRUMENT_REGION();
+
+        CV_OCL_RUN(isUmat_,
+                   ocl_processFrame(idx))
+
+        const int startIdx = std::max(idx - temporalAreaRadius_, 0);
+        const int procIdx = idx;
+        const int endIdx = std::min(startIdx + 2 * temporalAreaRadius_, storePos_);
+
+        const int count = endIdx - startIdx + 1;
+
+        srcFrames_.resize(count);
+        srcForwardMotions_.resize(count);
+        srcBackwardMotions_.resize(count);
+
+        int baseIdx = -1;
+
+        for (int i = startIdx, k = 0; i <= endIdx; ++i, ++k)
+        {
+            if (i == procIdx)
+                baseIdx = k;
+
+            srcFrames_[k] = at(i, frames_);
+
+            if (i < endIdx)
+                srcForwardMotions_[k] = at(i, forwardMotions_);
+            if (i > startIdx)
+                srcBackwardMotions_[k] = at(i, backwardMotions_);
+        }
+
+        process(srcFrames_, at(idx, outputs_), srcForwardMotions_, srcBackwardMotions_, baseIdx);
+    }
+}
+
+Ptr<cv::superres::SuperResolution> cv::superres::createSuperResolution_BTVL1()
+{
+    return makePtr<BTVL1>();
+}

modules/superres/src/btv_l1_cuda.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+// S. Farsiu , D. Robinson, M. Elad, P. Milanfar. Fast and robust multiframe super resolution.
+// Dennis Mitzel, Thomas Pock, Thomas Schoenemann, Daniel Cremers. Video Super Resolution using Duality Based TV-L1 Optical Flow.
+
+#include "precomp.hpp"
+
+using namespace cv;
+using namespace cv::cuda;
+using namespace cv::superres;
+using namespace cv::superres::detail;
+
+#if !defined(HAVE_CUDA) || !defined(HAVE_OPENCV_CUDAARITHM) || !defined(HAVE_OPENCV_CUDAWARPING) || !defined(HAVE_OPENCV_CUDAFILTERS)
+
+Ptr<SuperResolution> cv::superres::createSuperResolution_BTVL1_CUDA()
+{
+    CV_Error(Error::StsNotImplemented, "The called functionality is disabled for current build or platform");
+}
+
+#else // HAVE_CUDA
+
+namespace btv_l1_cudev
+{
+    void buildMotionMaps(PtrStepSzf forwardMotionX, PtrStepSzf forwardMotionY,
+                         PtrStepSzf backwardMotionX, PtrStepSzf bacwardMotionY,
+                         PtrStepSzf forwardMapX, PtrStepSzf forwardMapY,
+                         PtrStepSzf backwardMapX, PtrStepSzf backwardMapY);
+
+    template <int cn>
+    void upscale(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
+
+    void diffSign(PtrStepSzf src1, PtrStepSzf src2, PtrStepSzf dst, cudaStream_t stream);
+
+    void loadBtvWeights(const float* weights, size_t count);
+    template <int cn> void calcBtvRegularization(PtrStepSzb src, PtrStepSzb dst, int ksize);
+}
+
+namespace
+{
+    void calcRelativeMotions(const std::vector<std::pair<GpuMat, GpuMat> >& forwardMotions, const std::vector<std::pair<GpuMat, GpuMat> >& backwardMotions,
+                             std::vector<std::pair<GpuMat, GpuMat> >& relForwardMotions, std::vector<std::pair<GpuMat, GpuMat> >& relBackwardMotions,
+                             int baseIdx, Size size)
+    {
+        const int count = static_cast<int>(forwardMotions.size());
+
+        relForwardMotions.resize(count);
+        relForwardMotions[baseIdx].first.create(size, CV_32FC1);
+        relForwardMotions[baseIdx].first.setTo(Scalar::all(0));
+        relForwardMotions[baseIdx].second.create(size, CV_32FC1);
+        relForwardMotions[baseIdx].second.setTo(Scalar::all(0));
+
+        relBackwardMotions.resize(count);
+        relBackwardMotions[baseIdx].first.create(size, CV_32FC1);
+        relBackwardMotions[baseIdx].first.setTo(Scalar::all(0));
+        relBackwardMotions[baseIdx].second.create(size, CV_32FC1);
+        relBackwardMotions[baseIdx].second.setTo(Scalar::all(0));
+
+        for (int i = baseIdx - 1; i >= 0; --i)
+        {
+            cuda::add(relForwardMotions[i + 1].first, forwardMotions[i].first, relForwardMotions[i].first);
+            cuda::add(relForwardMotions[i + 1].second, forwardMotions[i].second, relForwardMotions[i].second);
+
+            cuda::add(relBackwardMotions[i + 1].first, backwardMotions[i + 1].first, relBackwardMotions[i].first);
+            cuda::add(relBackwardMotions[i + 1].second, backwardMotions[i + 1].second, relBackwardMotions[i].second);
+        }
+
+        for (int i = baseIdx + 1; i < count; ++i)
+        {
+            cuda::add(relForwardMotions[i - 1].first, backwardMotions[i].first, relForwardMotions[i].first);
+            cuda::add(relForwardMotions[i - 1].second, backwardMotions[i].second, relForwardMotions[i].second);
+
+            cuda::add(relBackwardMotions[i - 1].first, forwardMotions[i - 1].first, relBackwardMotions[i].first);
+            cuda::add(relBackwardMotions[i - 1].second, forwardMotions[i - 1].second, relBackwardMotions[i].second);
+        }
+    }
+
+    void upscaleMotions(const std::vector<std::pair<GpuMat, GpuMat> >& lowResMotions, std::vector<std::pair<GpuMat, GpuMat> >& highResMotions, int scale)
+    {
+        highResMotions.resize(lowResMotions.size());
+
+        for (size_t i = 0; i < lowResMotions.size(); ++i)
+        {
+            cuda::resize(lowResMotions[i].first, highResMotions[i].first, Size(), scale, scale, INTER_CUBIC);
+            cuda::resize(lowResMotions[i].second, highResMotions[i].second, Size(), scale, scale, INTER_CUBIC);
+
+            cuda::multiply(highResMotions[i].first, Scalar::all(scale), highResMotions[i].first);
+            cuda::multiply(highResMotions[i].second, Scalar::all(scale), highResMotions[i].second);
+        }
+    }
+
+    void buildMotionMaps(const std::pair<GpuMat, GpuMat>& forwardMotion, const std::pair<GpuMat, GpuMat>& backwardMotion,
+                         std::pair<GpuMat, GpuMat>& forwardMap, std::pair<GpuMat, GpuMat>& backwardMap)
+    {
+        forwardMap.first.create(forwardMotion.first.size(), CV_32FC1);
+        forwardMap.second.create(forwardMotion.first.size(), CV_32FC1);
+
+        backwardMap.first.create(forwardMotion.first.size(), CV_32FC1);
+        backwardMap.second.create(forwardMotion.first.size(), CV_32FC1);
+
+        btv_l1_cudev::buildMotionMaps(forwardMotion.first, forwardMotion.second,
+                                       backwardMotion.first, backwardMotion.second,
+                                       forwardMap.first, forwardMap.second,
+                                       backwardMap.first, backwardMap.second);
+    }
+
+    void upscale(const GpuMat& src, GpuMat& dst, int scale, Stream& stream)
+    {
+        typedef void (*func_t)(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
+        static const func_t funcs[] =
+        {
+            0, btv_l1_cudev::upscale<1>, 0, btv_l1_cudev::upscale<3>, btv_l1_cudev::upscale<4>
+        };
+
+        CV_Assert( src.channels() == 1 || src.channels() == 3 || src.channels() == 4 );
+
+        dst.create(src.rows * scale, src.cols * scale, src.type());
+        dst.setTo(Scalar::all(0));
+
+        const func_t func = funcs[src.channels()];
+
+        func(src, dst, scale, StreamAccessor::getStream(stream));
+    }
+
+    void diffSign(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
+    {
+        dst.create(src1.size(), src1.type());
+
+        btv_l1_cudev::diffSign(src1.reshape(1), src2.reshape(1), dst.reshape(1), StreamAccessor::getStream(stream));
+    }
+
+    void calcBtvWeights(int btvKernelSize, double alpha, std::vector<float>& btvWeights)
+    {
+        const size_t size = btvKernelSize * btvKernelSize;
+
+        btvWeights.resize(size);
+
+        const int ksize = (btvKernelSize - 1) / 2;
+        const float alpha_f = static_cast<float>(alpha);
+
+        for (int m = 0, ind = 0; m <= ksize; ++m)
+        {
+            for (int l = ksize; l + m >= 0; --l, ++ind)
+                btvWeights[ind] = pow(alpha_f, std::abs(m) + std::abs(l));
+        }
+
+        btv_l1_cudev::loadBtvWeights(&btvWeights[0], size);
+    }
+
+    void calcBtvRegularization(const GpuMat& src, GpuMat& dst, int btvKernelSize)
+    {
+        typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, int ksize);
+        static const func_t funcs[] =
+        {
+            0,
+            btv_l1_cudev::calcBtvRegularization<1>,
+            0,
+            btv_l1_cudev::calcBtvRegularization<3>,
+            btv_l1_cudev::calcBtvRegularization<4>
+        };
+
+        dst.create(src.size(), src.type());
+        dst.setTo(Scalar::all(0));
+
+        const int ksize = (btvKernelSize - 1) / 2;
+
+        funcs[src.channels()](src, dst, ksize);
+    }
+
+    class BTVL1_CUDA_Base : public cv::superres::SuperResolution
+    {
+    public:
+        BTVL1_CUDA_Base();
+
+        void process(const std::vector<GpuMat>& src, GpuMat& dst,
+                     const std::vector<std::pair<GpuMat, GpuMat> >& forwardMotions, const std::vector<std::pair<GpuMat, GpuMat> >& backwardMotions,
+                     int baseIdx);
+
+        void collectGarbage();
+
+        inline int getScale() const CV_OVERRIDE { return scale_; }
+        inline void setScale(int val) CV_OVERRIDE { scale_ = val; }
+        inline int getIterations() const CV_OVERRIDE { return iterations_; }
+        inline void setIterations(int val) CV_OVERRIDE { iterations_ = val; }
+        inline double getTau() const CV_OVERRIDE { return tau_; }
+        inline void setTau(double val) CV_OVERRIDE { tau_ = val; }
+        inline double getLabmda() const CV_OVERRIDE { return lambda_; }
+        inline void setLabmda(double val) CV_OVERRIDE { lambda_ = val; }
+        inline double getAlpha() const CV_OVERRIDE { return alpha_; }
+        inline void setAlpha(double val) CV_OVERRIDE { alpha_ = val; }
+        inline int getKernelSize() const CV_OVERRIDE { return btvKernelSize_; }
+        inline void setKernelSize(int val) CV_OVERRIDE { btvKernelSize_ = val; }
+        inline int getBlurKernelSize() const CV_OVERRIDE { return blurKernelSize_; }
+        inline void setBlurKernelSize(int val) CV_OVERRIDE { blurKernelSize_ = val; }
+        inline double getBlurSigma() const CV_OVERRIDE { return blurSigma_; }
+        inline void setBlurSigma(double val) CV_OVERRIDE { blurSigma_ = val; }
+        inline int getTemporalAreaRadius() const CV_OVERRIDE { return temporalAreaRadius_; }
+        inline void setTemporalAreaRadius(int val) CV_OVERRIDE { temporalAreaRadius_ = val; }
+        inline Ptr<cv::superres::DenseOpticalFlowExt> getOpticalFlow() const CV_OVERRIDE { return opticalFlow_; }
+        inline void setOpticalFlow(const Ptr<cv::superres::DenseOpticalFlowExt>& val) CV_OVERRIDE { opticalFlow_ = val; }
+
+    protected:
+        int scale_;
+        int iterations_;
+        double lambda_;
+        double tau_;
+        double alpha_;
+        int btvKernelSize_;
+        int blurKernelSize_;
+        double blurSigma_;
+        int temporalAreaRadius_;
+        Ptr<cv::superres::DenseOpticalFlowExt> opticalFlow_;
+
+    private:
+        std::vector<Ptr<cuda::Filter> > filters_;
+        int curBlurKernelSize_;
+        double curBlurSigma_;
+        int curSrcType_;
+
+        std::vector<float> btvWeights_;
+        int curBtvKernelSize_;
+        double curAlpha_;
+
+        std::vector<std::pair<GpuMat, GpuMat> > lowResForwardMotions_;
+        std::vector<std::pair<GpuMat, GpuMat> > lowResBackwardMotions_;
+
+        std::vector<std::pair<GpuMat, GpuMat> > highResForwardMotions_;
+        std::vector<std::pair<GpuMat, GpuMat> > highResBackwardMotions_;
+
+        std::vector<std::pair<GpuMat, GpuMat> > forwardMaps_;
+        std::vector<std::pair<GpuMat, GpuMat> > backwardMaps_;
+
+        GpuMat highRes_;
+
+        std::vector<Stream> streams_;
+        std::vector<GpuMat> diffTerms_;
+        std::vector<GpuMat> a_, b_, c_;
+        GpuMat regTerm_;
+    };
+
+    BTVL1_CUDA_Base::BTVL1_CUDA_Base()
+    {
+        scale_ = 4;
+        iterations_ = 180;
+        lambda_ = 0.03;
+        tau_ = 1.3;
+        alpha_ = 0.7;
+        btvKernelSize_ = 7;
+        blurKernelSize_ = 5;
+        blurSigma_ = 0.0;
+
+#ifdef HAVE_OPENCV_CUDAOPTFLOW
+        opticalFlow_ = createOptFlow_Farneback_CUDA();
+#else
+        opticalFlow_ = createOptFlow_Farneback();
+#endif
+        temporalAreaRadius_ = 0;
+
+        curBlurKernelSize_ = -1;
+        curBlurSigma_ = -1.0;
+        curSrcType_ = -1;
+
+        curBtvKernelSize_ = -1;
+        curAlpha_ = -1.0;
+    }
+
+    void BTVL1_CUDA_Base::process(const std::vector<GpuMat>& src, GpuMat& dst,
+                                 const std::vector<std::pair<GpuMat, GpuMat> >& forwardMotions, const std::vector<std::pair<GpuMat, GpuMat> >& backwardMotions,
+                                 int baseIdx)
+    {
+        CV_Assert( scale_ > 1 );
+        CV_Assert( iterations_ > 0 );
+        CV_Assert( tau_ > 0.0 );
+        CV_Assert( alpha_ > 0.0 );
+        CV_Assert( btvKernelSize_ > 0 && btvKernelSize_ <= 16 );
+        CV_Assert( blurKernelSize_ > 0 );
+        CV_Assert( blurSigma_ >= 0.0 );
+
+        // update blur filter and btv weights
+
+        if (filters_.size() != src.size() || blurKernelSize_ != curBlurKernelSize_ || blurSigma_ != curBlurSigma_ || src[0].type() != curSrcType_)
+        {
+            filters_.resize(src.size());
+            for (size_t i = 0; i < src.size(); ++i)
+                filters_[i] = cuda::createGaussianFilter(src[0].type(), -1, Size(blurKernelSize_, blurKernelSize_), blurSigma_);
+            curBlurKernelSize_ = blurKernelSize_;
+            curBlurSigma_ = blurSigma_;
+            curSrcType_ = src[0].type();
+        }
+
+        if (btvWeights_.empty() || btvKernelSize_ != curBtvKernelSize_ || alpha_ != curAlpha_)
+        {
+            calcBtvWeights(btvKernelSize_, alpha_, btvWeights_);
+            curBtvKernelSize_ = btvKernelSize_;
+            curAlpha_ = alpha_;
+        }
+
+        // calc motions between input frames
+
+        calcRelativeMotions(forwardMotions, backwardMotions, lowResForwardMotions_, lowResBackwardMotions_, baseIdx, src[0].size());
+
+        upscaleMotions(lowResForwardMotions_, highResForwardMotions_, scale_);
+        upscaleMotions(lowResBackwardMotions_, highResBackwardMotions_, scale_);
+
+        forwardMaps_.resize(highResForwardMotions_.size());
+        backwardMaps_.resize(highResForwardMotions_.size());
+        for (size_t i = 0; i < highResForwardMotions_.size(); ++i)
+            buildMotionMaps(highResForwardMotions_[i], highResBackwardMotions_[i], forwardMaps_[i], backwardMaps_[i]);
+
+        // initial estimation
+
+        const Size lowResSize = src[0].size();
+        const Size highResSize(lowResSize.width * scale_, lowResSize.height * scale_);
+
+        cuda::resize(src[baseIdx], highRes_, highResSize, 0, 0, INTER_CUBIC);
+
+        // iterations
+
+        streams_.resize(src.size());
+        diffTerms_.resize(src.size());
+        a_.resize(src.size());
+        b_.resize(src.size());
+        c_.resize(src.size());
+
+        for (int i = 0; i < iterations_; ++i)
+        {
+            for (size_t k = 0; k < src.size(); ++k)
+            {
+                // a = M * Ih
+                cuda::remap(highRes_, a_[k], backwardMaps_[k].first, backwardMaps_[k].second, INTER_NEAREST, BORDER_REPLICATE, Scalar(), streams_[k]);
+                // b = HM * Ih
+                filters_[k]->apply(a_[k], b_[k], streams_[k]);
+                // c = DHF * Ih
+                cuda::resize(b_[k], c_[k], lowResSize, 0, 0, INTER_NEAREST, streams_[k]);
+
+                diffSign(src[k], c_[k], c_[k], streams_[k]);
+
+                // a = Dt * diff
+                upscale(c_[k], a_[k], scale_, streams_[k]);
+                // b = HtDt * diff
+                filters_[k]->apply(a_[k], b_[k], streams_[k]);
+                // diffTerm = MtHtDt * diff
+                cuda::remap(b_[k], diffTerms_[k], forwardMaps_[k].first, forwardMaps_[k].second, INTER_NEAREST, BORDER_REPLICATE, Scalar(), streams_[k]);
+            }
+
+            if (lambda_ > 0)
+            {
+                calcBtvRegularization(highRes_, regTerm_, btvKernelSize_);
+                cuda::addWeighted(highRes_, 1.0, regTerm_, -tau_ * lambda_, 0.0, highRes_);
+            }
+
+            for (size_t k = 0; k < src.size(); ++k)
+            {
+                streams_[k].waitForCompletion();
+                cuda::addWeighted(highRes_, 1.0, diffTerms_[k], tau_, 0.0, highRes_);
+            }
+        }
+
+        Rect inner(btvKernelSize_, btvKernelSize_, highRes_.cols - 2 * btvKernelSize_, highRes_.rows - 2 * btvKernelSize_);
+        highRes_(inner).copyTo(dst);
+    }
+
+    void BTVL1_CUDA_Base::collectGarbage()
+    {
+        filters_.clear();
+
+        lowResForwardMotions_.clear();
+        lowResBackwardMotions_.clear();
+
+        highResForwardMotions_.clear();
+        highResBackwardMotions_.clear();
+
+        forwardMaps_.clear();
+        backwardMaps_.clear();
+
+        highRes_.release();
+
+        diffTerms_.clear();
+        a_.clear();
+        b_.clear();
+        c_.clear();
+        regTerm_.release();
+    }
+
+////////////////////////////////////////////////////////////
+
+    class BTVL1_CUDA : public BTVL1_CUDA_Base
+    {
+    public:
+        BTVL1_CUDA();
+
+        void collectGarbage();
+
+    protected:
+        void initImpl(Ptr<FrameSource>& frameSource);
+        void processImpl(Ptr<FrameSource>& frameSource, OutputArray output);
+
+    private:
+        void readNextFrame(Ptr<FrameSource>& frameSource);
+        void processFrame(int idx);
+
+        GpuMat curFrame_;
+        GpuMat prevFrame_;
+
+        std::vector<GpuMat> frames_;
+        std::vector<std::pair<GpuMat, GpuMat> > forwardMotions_;
+        std::vector<std::pair<GpuMat, GpuMat> > backwardMotions_;
+        std::vector<GpuMat> outputs_;
+
+        int storePos_;
+        int procPos_;
+        int outPos_;
+
+        std::vector<GpuMat> srcFrames_;
+        std::vector<std::pair<GpuMat, GpuMat> > srcForwardMotions_;
+        std::vector<std::pair<GpuMat, GpuMat> > srcBackwardMotions_;
+        GpuMat finalOutput_;
+    };
+
+    BTVL1_CUDA::BTVL1_CUDA()
+    {
+        temporalAreaRadius_ = 4;
+    }
+
+    void BTVL1_CUDA::collectGarbage()
+    {
+        curFrame_.release();
+        prevFrame_.release();
+
+        frames_.clear();
+        forwardMotions_.clear();
+        backwardMotions_.clear();
+        outputs_.clear();
+
+        srcFrames_.clear();
+        srcForwardMotions_.clear();
+        srcBackwardMotions_.clear();
+        finalOutput_.release();
+
+        SuperResolution::collectGarbage();
+        BTVL1_CUDA_Base::collectGarbage();
+    }
+
+    void BTVL1_CUDA::initImpl(Ptr<FrameSource>& frameSource)
+    {
+        const int cacheSize = 2 * temporalAreaRadius_ + 1;
+
+        frames_.resize(cacheSize);
+        forwardMotions_.resize(cacheSize);
+        backwardMotions_.resize(cacheSize);
+        outputs_.resize(cacheSize);
+
+        storePos_ = -1;
+
+        for (int t = -temporalAreaRadius_; t <= temporalAreaRadius_; ++t)
+            readNextFrame(frameSource);
+
+        for (int i = 0; i <= temporalAreaRadius_; ++i)
+            processFrame(i);
+
+        procPos_ = temporalAreaRadius_;
+        outPos_ = -1;
+    }
+
+    void BTVL1_CUDA::processImpl(Ptr<FrameSource>& frameSource, OutputArray _output)
+    {
+        if (outPos_ >= storePos_)
+        {
+            _output.release();
+            return;
+        }
+
+        readNextFrame(frameSource);
+
+        if (procPos_ < storePos_)
+        {
+            ++procPos_;
+            processFrame(procPos_);
+        }
+
+        ++outPos_;
+        const GpuMat& curOutput = at(outPos_, outputs_);
+
+        if (_output.kind() == _InputArray::CUDA_GPU_MAT)
+            curOutput.convertTo(_output.getGpuMatRef(), CV_8U);
+        else
+        {
+            curOutput.convertTo(finalOutput_, CV_8U);
+            arrCopy(finalOutput_, _output);
+        }
+    }
+
+    void BTVL1_CUDA::readNextFrame(Ptr<FrameSource>& frameSource)
+    {
+        frameSource->nextFrame(curFrame_);
+
+        if (curFrame_.empty())
+            return;
+
+        ++storePos_;
+        curFrame_.convertTo(at(storePos_, frames_), CV_32F);
+
+        if (storePos_ > 0)
+        {
+            std::pair<GpuMat, GpuMat>& forwardMotion = at(storePos_ - 1, forwardMotions_);
+            std::pair<GpuMat, GpuMat>& backwardMotion = at(storePos_, backwardMotions_);
+
+            opticalFlow_->calc(prevFrame_, curFrame_, forwardMotion.first, forwardMotion.second);
+            opticalFlow_->calc(curFrame_, prevFrame_, backwardMotion.first, backwardMotion.second);
+        }
+
+        curFrame_.copyTo(prevFrame_);
+    }
+
+    void BTVL1_CUDA::processFrame(int idx)
+    {
+        const int startIdx = std::max(idx - temporalAreaRadius_, 0);
+        const int procIdx = idx;
+        const int endIdx = std::min(startIdx + 2 * temporalAreaRadius_, storePos_);
+
+        const int count = endIdx - startIdx + 1;
+
+        srcFrames_.resize(count);
+        srcForwardMotions_.resize(count);
+        srcBackwardMotions_.resize(count);
+
+        int baseIdx = -1;
+
+        for (int i = startIdx, k = 0; i <= endIdx; ++i, ++k)
+        {
+            if (i == procIdx)
+                baseIdx = k;
+
+            srcFrames_[k] = at(i, frames_);
+
+            if (i < endIdx)
+                srcForwardMotions_[k] = at(i, forwardMotions_);
+            if (i > startIdx)
+                srcBackwardMotions_[k] = at(i, backwardMotions_);
+        }
+
+        process(srcFrames_, at(idx, outputs_), srcForwardMotions_, srcBackwardMotions_, baseIdx);
+    }
+}
+
+Ptr<SuperResolution> cv::superres::createSuperResolution_BTVL1_CUDA()
+{
+    return makePtr<BTVL1_CUDA>();
+}
+
+#endif // HAVE_CUDA

modules/superres/src/cuda/btv_l1_gpu.cu

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "opencv2/opencv_modules.hpp"
+
+#if defined(HAVE_OPENCV_CUDAARITHM) && defined(HAVE_OPENCV_CUDAWARPING) && defined(HAVE_OPENCV_CUDAFILTERS)
+
+#include "opencv2/core/cuda/common.hpp"
+#include "opencv2/core/cuda/transform.hpp"
+#include "opencv2/core/cuda/vec_traits.hpp"
+#include "opencv2/core/cuda/vec_math.hpp"
+
+using namespace cv::cuda;
+using namespace cv::cuda::device;
+
+namespace btv_l1_cudev
+{
+    void buildMotionMaps(PtrStepSzf forwardMotionX, PtrStepSzf forwardMotionY,
+                         PtrStepSzf backwardMotionX, PtrStepSzf bacwardMotionY,
+                         PtrStepSzf forwardMapX, PtrStepSzf forwardMapY,
+                         PtrStepSzf backwardMapX, PtrStepSzf backwardMapY);
+
+    template <int cn>
+    void upscale(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
+
+    void diffSign(PtrStepSzf src1, PtrStepSzf src2, PtrStepSzf dst, cudaStream_t stream);
+
+    void loadBtvWeights(const float* weights, size_t count);
+    template <int cn> void calcBtvRegularization(PtrStepSzb src, PtrStepSzb dst, int ksize);
+}
+
+namespace btv_l1_cudev
+{
+    __global__ void buildMotionMapsKernel(const PtrStepSzf forwardMotionX, const PtrStepf forwardMotionY,
+                                          PtrStepf backwardMotionX, PtrStepf backwardMotionY,
+                                          PtrStepf forwardMapX, PtrStepf forwardMapY,
+                                          PtrStepf backwardMapX, PtrStepf backwardMapY)
+    {
+        const int x = blockIdx.x * blockDim.x + threadIdx.x;
+        const int y = blockIdx.y * blockDim.y + threadIdx.y;
+
+        if (x >= forwardMotionX.cols || y >= forwardMotionX.rows)
+            return;
+
+        const float fx = forwardMotionX(y, x);
+        const float fy = forwardMotionY(y, x);
+
+        const float bx = backwardMotionX(y, x);
+        const float by = backwardMotionY(y, x);
+
+        forwardMapX(y, x) = x + bx;
+        forwardMapY(y, x) = y + by;
+
+        backwardMapX(y, x) = x + fx;
+        backwardMapY(y, x) = y + fy;
+    }
+
+    void buildMotionMaps(PtrStepSzf forwardMotionX, PtrStepSzf forwardMotionY,
+                         PtrStepSzf backwardMotionX, PtrStepSzf bacwardMotionY,
+                         PtrStepSzf forwardMapX, PtrStepSzf forwardMapY,
+                         PtrStepSzf backwardMapX, PtrStepSzf backwardMapY)
+    {
+        const dim3 block(32, 8);
+        const dim3 grid(divUp(forwardMapX.cols, block.x), divUp(forwardMapX.rows, block.y));
+
+        buildMotionMapsKernel<<<grid, block>>>(forwardMotionX, forwardMotionY,
+                                               backwardMotionX, bacwardMotionY,
+                                               forwardMapX, forwardMapY,
+                                               backwardMapX, backwardMapY);
+        cudaSafeCall( cudaGetLastError() );
+
+        cudaSafeCall( cudaDeviceSynchronize() );
+    }
+
+    template <typename T>
+    __global__ void upscaleKernel(const PtrStepSz<T> src, PtrStep<T> dst, const int scale)
+    {
+        const int x = blockIdx.x * blockDim.x + threadIdx.x;
+        const int y = blockIdx.y * blockDim.y + threadIdx.y;
+
+        if (x >= src.cols || y >= src.rows)
+            return;
+
+        dst(y * scale, x * scale) = src(y, x);
+    }
+
+    template <int cn>
+    void upscale(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream)
+    {
+        typedef typename TypeVec<float, cn>::vec_type src_t;
+
+        const dim3 block(32, 8);
+        const dim3 grid(divUp(src.cols, block.x), divUp(src.rows, block.y));
+
+        upscaleKernel<src_t><<<grid, block, 0, stream>>>((PtrStepSz<src_t>) src, (PtrStepSz<src_t>) dst, scale);
+        cudaSafeCall( cudaGetLastError() );
+
+        if (stream == 0)
+            cudaSafeCall( cudaDeviceSynchronize() );
+    }
+
+    template void upscale<1>(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
+    template void upscale<3>(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
+    template void upscale<4>(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
+
+    __device__ __forceinline__ float diffSign(float a, float b)
+    {
+        return a > b ? 1.0f : a < b ? -1.0f : 0.0f;
+    }
+    __device__ __forceinline__ float3 diffSign(const float3& a, const float3& b)
+    {
+        return make_float3(
+            a.x > b.x ? 1.0f : a.x < b.x ? -1.0f : 0.0f,
+            a.y > b.y ? 1.0f : a.y < b.y ? -1.0f : 0.0f,
+            a.z > b.z ? 1.0f : a.z < b.z ? -1.0f : 0.0f
+        );
+    }
+    __device__ __forceinline__ float4 diffSign(const float4& a, const float4& b)
+    {
+        return make_float4(
+            a.x > b.x ? 1.0f : a.x < b.x ? -1.0f : 0.0f,
+            a.y > b.y ? 1.0f : a.y < b.y ? -1.0f : 0.0f,
+            a.z > b.z ? 1.0f : a.z < b.z ? -1.0f : 0.0f,
+            0.0f
+        );
+    }
+
+    struct DiffSign : binary_function<float, float, float>
+    {
+        __device__ __forceinline__ float operator ()(float a, float b) const
+        {
+            return diffSign(a, b);
+        }
+    };
+}
+
+namespace cv { namespace cuda { namespace device
+{
+    template <> struct TransformFunctorTraits<btv_l1_cudev::DiffSign> : DefaultTransformFunctorTraits<btv_l1_cudev::DiffSign>
+    {
+        enum { smart_block_dim_y = 8 };
+        enum { smart_shift = 4 };
+    };
+}}}
+
+namespace btv_l1_cudev
+{
+    void diffSign(PtrStepSzf src1, PtrStepSzf src2, PtrStepSzf dst, cudaStream_t stream)
+    {
+        transform(src1, src2, dst, DiffSign(), WithOutMask(), stream);
+    }
+
+    __constant__ float c_btvRegWeights[16*16];
+
+    template <typename T>
+    __global__ void calcBtvRegularizationKernel(const PtrStepSz<T> src, PtrStep<T> dst, const int ksize)
+    {
+        const int x = blockIdx.x * blockDim.x + threadIdx.x + ksize;
+        const int y = blockIdx.y * blockDim.y + threadIdx.y + ksize;
+
+        if (y >= src.rows - ksize || x >= src.cols - ksize)
+            return;
+
+        const T srcVal = src(y, x);
+
+        T dstVal = VecTraits<T>::all(0);
+
+        for (int m = 0, count = 0; m <= ksize; ++m)
+        {
+            for (int l = ksize; l + m >= 0; --l, ++count)
+                dstVal = dstVal + c_btvRegWeights[count] * (diffSign(srcVal, src(y + m, x + l)) - diffSign(src(y - m, x - l), srcVal));
+        }
+
+        dst(y, x) = dstVal;
+    }
+
+    void loadBtvWeights(const float* weights, size_t count)
+    {
+        cudaSafeCall( cudaMemcpyToSymbol(c_btvRegWeights, weights, count * sizeof(float)) );
+    }
+
+    template <int cn>
+    void calcBtvRegularization(PtrStepSzb src, PtrStepSzb dst, int ksize)
+    {
+        typedef typename TypeVec<float, cn>::vec_type src_t;
+
+        const dim3 block(32, 8);
+        const dim3 grid(divUp(src.cols, block.x), divUp(src.rows, block.y));
+
+        calcBtvRegularizationKernel<src_t><<<grid, block>>>((PtrStepSz<src_t>) src, (PtrStepSz<src_t>) dst, ksize);
+        cudaSafeCall( cudaGetLastError() );
+
+        cudaSafeCall( cudaDeviceSynchronize() );
+    }
+
+    template void calcBtvRegularization<1>(PtrStepSzb src, PtrStepSzb dst, int ksize);
+    template void calcBtvRegularization<3>(PtrStepSzb src, PtrStepSzb dst, int ksize);
+    template void calcBtvRegularization<4>(PtrStepSzb src, PtrStepSzb dst, int ksize);
+}
+
+#endif

modules/superres/src/frame_source.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+#include "precomp.hpp"
+
+using namespace cv;
+using namespace cv::cuda;
+using namespace cv::superres;
+using namespace cv::superres::detail;
+
+cv::superres::FrameSource::~FrameSource()
+{
+}
+
+//////////////////////////////////////////////////////
+// EmptyFrameSource
+
+namespace
+{
+    class EmptyFrameSource : public FrameSource
+    {
+    public:
+        void nextFrame(OutputArray frame) CV_OVERRIDE;
+        void reset() CV_OVERRIDE;
+    };
+
+    void EmptyFrameSource::nextFrame(OutputArray frame)
+    {
+        frame.release();
+    }
+
+    void EmptyFrameSource::reset()
+    {
+    }
+}
+
+Ptr<FrameSource> cv::superres::createFrameSource_Empty()
+{
+    return makePtr<EmptyFrameSource>();
+}
+
+//////////////////////////////////////////////////////
+// VideoFrameSource & CameraFrameSource
+
+#ifndef HAVE_OPENCV_VIDEOIO
+
+Ptr<FrameSource> cv::superres::createFrameSource_Video(const String& fileName)
+{
+    CV_UNUSED(fileName);
+    CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform");
+    return Ptr<FrameSource>();
+}
+
+Ptr<FrameSource> cv::superres::createFrameSource_Camera(int deviceId)
+{
+    CV_UNUSED(deviceId);
+    CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform");
+    return Ptr<FrameSource>();
+}
+
+#else // HAVE_OPENCV_VIDEOIO
+
+namespace
+{
+    class CaptureFrameSource : public FrameSource
+    {
+    public:
+        void nextFrame(OutputArray frame) CV_OVERRIDE;
+
+    protected:
+        VideoCapture vc_;
+
+    private:
+        Mat frame_;
+    };
+
+    void CaptureFrameSource::nextFrame(OutputArray _frame)
+    {
+        if (_frame.kind() == _InputArray::MAT)
+            vc_ >> _frame.getMatRef();
+        else if(_frame.kind() == _InputArray::CUDA_GPU_MAT)
+        {
+            vc_ >> frame_;
+            arrCopy(frame_, _frame);
+        }
+        else if (_frame.isUMat())
+            vc_ >> *(UMat *)_frame.getObj();
+        else
+        {
+            // should never get here
+            CV_Error(Error::StsBadArg, "Failed to detect input frame kind" );
+        }
+    }
+
+    class VideoFrameSource : public CaptureFrameSource
+    {
+    public:
+        VideoFrameSource(const String& fileName);
+
+        void reset() CV_OVERRIDE;
+
+    private:
+        String fileName_;
+    };
+
+    VideoFrameSource::VideoFrameSource(const String& fileName) : fileName_(fileName)
+    {
+        reset();
+    }
+
+    void VideoFrameSource::reset()
+    {
+        vc_.release();
+        vc_.open(fileName_);
+        CV_Assert( vc_.isOpened() );
+    }
+
+    class CameraFrameSource : public CaptureFrameSource
+    {
+    public:
+        CameraFrameSource(int deviceId);
+
+        void reset() CV_OVERRIDE;
+
+    private:
+        int deviceId_;
+    };
+
+    CameraFrameSource::CameraFrameSource(int deviceId) : deviceId_(deviceId)
+    {
+        reset();
+    }
+
+    void CameraFrameSource::reset()
+    {
+        vc_.release();
+        vc_.open(deviceId_);
+        CV_Assert( vc_.isOpened() );
+    }
+}
+
+Ptr<FrameSource> cv::superres::createFrameSource_Video(const String& fileName)
+{
+    return makePtr<VideoFrameSource>(fileName);
+}
+
+Ptr<FrameSource> cv::superres::createFrameSource_Camera(int deviceId)
+{
+    return makePtr<CameraFrameSource>(deviceId);
+}
+
+#endif // HAVE_OPENCV_VIDEOIO
+
+//////////////////////////////////////////////////////
+// VideoFrameSource_CUDA
+
+#ifndef HAVE_OPENCV_CUDACODEC
+
+Ptr<FrameSource> cv::superres::createFrameSource_Video_CUDA(const String& fileName)
+{
+    CV_UNUSED(fileName);
+    CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform");
+}
+
+#else // HAVE_OPENCV_CUDACODEC
+
+namespace
+{
+    class VideoFrameSource_CUDA : public FrameSource
+    {
+    public:
+        VideoFrameSource_CUDA(const String& fileName);
+
+        void nextFrame(OutputArray frame);
+        void reset();
+
+    private:
+        String fileName_;
+        Ptr<cudacodec::VideoReader> reader_;
+        GpuMat frame_;
+    };
+
+    VideoFrameSource_CUDA::VideoFrameSource_CUDA(const String& fileName) : fileName_(fileName)
+    {
+        reset();
+    }
+
+    void VideoFrameSource_CUDA::nextFrame(OutputArray _frame)
+    {
+        if (_frame.kind() == _InputArray::CUDA_GPU_MAT)
+        {
+            bool res = reader_->nextFrame(_frame.getGpuMatRef());
+            if (!res)
+                _frame.release();
+        }
+        else
+        {
+            bool res = reader_->nextFrame(frame_);
+            if (!res)
+                _frame.release();
+            else
+                arrCopy(frame_, _frame);
+        }
+    }
+
+    void VideoFrameSource_CUDA::reset()
+    {
+        reader_ = cudacodec::createVideoReader(fileName_);
+    }
+}
+
+Ptr<FrameSource> cv::superres::createFrameSource_Video_CUDA(const String& fileName)
+{
+    return makePtr<VideoFrameSource_CUDA>(fileName);
+}
+
+#endif // HAVE_OPENCV_CUDACODEC

modules/superres/src/input_array_utility.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "precomp.hpp"
+
+using namespace cv;
+using namespace cv::cuda;
+
+Mat cv::superres::arrGetMat(InputArray arr, Mat& buf)
+{
+    switch (arr.kind())
+    {
+    case _InputArray::CUDA_GPU_MAT:
+        arr.getGpuMat().download(buf);
+        return buf;
+
+    case _InputArray::OPENGL_BUFFER:
+        arr.getOGlBuffer().copyTo(buf);
+        return buf;
+
+    default:
+        return arr.getMat();
+    }
+}
+
+UMat cv::superres::arrGetUMat(InputArray arr, UMat& buf)
+{
+    switch (arr.kind())
+    {
+    case _InputArray::CUDA_GPU_MAT:
+        arr.getGpuMat().download(buf);
+        return buf;
+
+    case _InputArray::OPENGL_BUFFER:
+        arr.getOGlBuffer().copyTo(buf);
+        return buf;
+
+    default:
+        return arr.getUMat();
+    }
+}
+
+GpuMat cv::superres::arrGetGpuMat(InputArray arr, GpuMat& buf)
+{
+    switch (arr.kind())
+    {
+    case _InputArray::CUDA_GPU_MAT:
+        return arr.getGpuMat();
+
+    case _InputArray::OPENGL_BUFFER:
+        arr.getOGlBuffer().copyTo(buf);
+        return buf;
+
+    default:
+        buf.upload(arr.getMat());
+        return buf;
+    }
+}
+
+namespace
+{
+    void mat2mat(InputArray src, OutputArray dst)
+    {
+        src.getMat().copyTo(dst);
+    }
+    void arr2buf(InputArray src, OutputArray dst)
+    {
+        dst.getOGlBufferRef().copyFrom(src);
+    }
+    void mat2gpu(InputArray src, OutputArray dst)
+    {
+        dst.getGpuMatRef().upload(src.getMat());
+    }
+    void buf2arr(InputArray src, OutputArray dst)
+    {
+        src.getOGlBuffer().copyTo(dst);
+    }
+    void gpu2mat(InputArray src, OutputArray dst)
+    {
+        GpuMat d = src.getGpuMat();
+        dst.create(d.size(), d.type());
+        Mat m = dst.getMat();
+        d.download(m);
+    }
+    void gpu2gpu(InputArray src, OutputArray dst)
+    {
+        src.getGpuMat().copyTo(dst.getGpuMatRef());
+    }
+}
+
+void cv::superres::arrCopy(InputArray src, OutputArray dst)
+{
+    if (dst.isUMat() || src.isUMat())
+    {
+        src.copyTo(dst);
+        return;
+    }
+
+    typedef void (*func_t)(InputArray src, OutputArray dst);
+    static const func_t funcs[10][10] =
+    {
+        { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
+        { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
+        { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
+        { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
+        { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
+        { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
+        { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu },
+        { 0, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, 0, buf2arr },
+        { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
+        { 0, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, arr2buf, 0 , gpu2gpu },
+    };
+
+    const int src_kind = src.kind() >> _InputArray::KIND_SHIFT;
+    const int dst_kind = dst.kind() >> _InputArray::KIND_SHIFT;
+
+    CV_Assert( src_kind >= 0 && src_kind < 10 );
+    CV_Assert( dst_kind >= 0 && dst_kind < 10 );
+
+    const func_t func = funcs[src_kind][dst_kind];
+    CV_Assert( func != 0 );
+
+    func(src, dst);
+}
+
+namespace
+{
+    void convertToCn(InputArray src, OutputArray dst, int cn)
+    {
+        int scn = src.channels();
+        CV_Assert( scn == 1 || scn == 3 || scn == 4 );
+        CV_Assert( cn == 1 || cn == 3 || cn == 4 );
+
+        static const int codes[5][5] =
+        {
+            { -1, -1, -1, -1, -1 },
+            { -1, -1, -1, COLOR_GRAY2BGR, COLOR_GRAY2BGRA },
+            { -1, -1, -1, -1, -1 },
+            { -1, COLOR_BGR2GRAY, -1, -1, COLOR_BGR2BGRA },
+            { -1, COLOR_BGRA2GRAY, -1, COLOR_BGRA2BGR, -1 }
+        };
+
+        const int code = codes[scn][cn];
+        CV_Assert( code >= 0 );
+
+        switch (src.kind())
+        {
+        case _InputArray::CUDA_GPU_MAT:
+            #ifdef HAVE_OPENCV_CUDAIMGPROC
+                cuda::cvtColor(src.getGpuMat(), dst.getGpuMatRef(), code, cn);
+            #else
+                CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform");
+            #endif
+            break;
+
+        default:
+            cv::cvtColor(src, dst, code, cn);
+            break;
+        }
+    }
+
+    void convertToDepth(InputArray src, OutputArray dst, int depth)
+    {
+        const int sdepth = src.depth();
+        CV_Assert( sdepth <= CV_64F );
+        CV_Assert( depth == CV_8U || depth == CV_32F );
+
+        static const double maxVals[CV_64F + 1] =
+        {
+            (double)std::numeric_limits<uchar>::max(),
+            (double)std::numeric_limits<schar>::max(),
+            (double)std::numeric_limits<ushort>::max(),
+            (double)std::numeric_limits<short>::max(),
+            (double)std::numeric_limits<int>::max(),
+            1.0,
+            1.0,
+        };
+
+        const double scale = maxVals[depth] / maxVals[sdepth];
+
+        switch (src.kind())
+        {
+        case _InputArray::CUDA_GPU_MAT:
+            src.getGpuMat().convertTo(dst.getGpuMatRef(), depth, scale);
+            break;
+
+        case _InputArray::UMAT:
+            src.getUMat().convertTo(dst, depth, scale);
+            break;
+
+        default:
+            src.getMat().convertTo(dst, depth, scale);
+            break;
+        }
+    }
+}
+
+Mat cv::superres::convertToType(const Mat& src, int type, Mat& buf0, Mat& buf1)
+{
+    CV_INSTRUMENT_REGION();
+
+    if (src.type() == type)
+        return src;
+
+    const int depth = CV_MAT_DEPTH(type);
+    const int cn = CV_MAT_CN(type);
+
+    if (src.depth() == depth)
+    {
+        convertToCn(src, buf0, cn);
+        return buf0;
+    }
+
+    if (src.channels() == cn)
+    {
+        convertToDepth(src, buf1, depth);
+        return buf1;
+    }
+
+    convertToCn(src, buf0, cn);
+    convertToDepth(buf0, buf1, depth);
+    return buf1;
+}
+
+UMat cv::superres::convertToType(const UMat& src, int type, UMat& buf0, UMat& buf1)
+{
+    CV_INSTRUMENT_REGION();
+
+    if (src.type() == type)
+        return src;
+
+    const int depth = CV_MAT_DEPTH(type);
+    const int cn = CV_MAT_CN(type);
+
+    if (src.depth() == depth)
+    {
+        convertToCn(src, buf0, cn);
+        return buf0;
+    }
+
+    if (src.channels() == cn)
+    {
+        convertToDepth(src, buf1, depth);
+        return buf1;
+    }
+
+    convertToCn(src, buf0, cn);
+    convertToDepth(buf0, buf1, depth);
+    return buf1;
+}
+
+GpuMat cv::superres::convertToType(const GpuMat& src, int type, GpuMat& buf0, GpuMat& buf1)
+{
+    if (src.type() == type)
+        return src;
+
+    const int depth = CV_MAT_DEPTH(type);
+    const int cn = CV_MAT_CN(type);
+
+    if (src.depth() == depth)
+    {
+        convertToCn(src, buf0, cn);
+        return buf0;
+    }
+
+    if (src.channels() == cn)
+    {
+        convertToDepth(src, buf1, depth);
+        return buf1;
+    }
+
+    convertToCn(src, buf0, cn);
+    convertToDepth(buf0, buf1, depth);
+    return buf1;
+}

modules/superres/src/input_array_utility.hpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef __OPENCV_SUPERRES_INPUT_ARRAY_UTILITY_HPP__
+#define __OPENCV_SUPERRES_INPUT_ARRAY_UTILITY_HPP__
+
+#include "opencv2/core.hpp"
+#include "opencv2/core/cuda.hpp"
+
+namespace cv
+{
+    namespace superres
+    {
+        CV_EXPORTS Mat arrGetMat(InputArray arr, Mat& buf);
+        CV_EXPORTS UMat arrGetUMat(InputArray arr, UMat& buf);
+        CV_EXPORTS cuda::GpuMat arrGetGpuMat(InputArray arr, cuda::GpuMat& buf);
+
+        CV_EXPORTS void arrCopy(InputArray src, OutputArray dst);
+
+        CV_EXPORTS Mat convertToType(const Mat& src, int type, Mat& buf0, Mat& buf1);
+        CV_EXPORTS UMat convertToType(const UMat& src, int type, UMat& buf0, UMat& buf1);
+        CV_EXPORTS cuda::GpuMat convertToType(const cuda::GpuMat& src, int type, cuda::GpuMat& buf0, cuda::GpuMat& buf1);
+    }
+}
+
+#endif // __OPENCV_SUPERRES_INPUT_ARRAY_UTILITY_HPP__

modules/superres/src/opencl/superres_btvl1.cl

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// @Authors
+//    Jin Ma jin@multicorewareinc.com
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef cn
+#define cn 1
+#endif
+
+#define sz (int)sizeof(float)
+#define src_elem_at(_src, y, step, x) *(__global const float *)(_src + mad24(y, step, (x) * sz))
+#define dst_elem_at(_dst, y, step, x) *(__global float *)(_dst + mad24(y, step, (x) * sz))
+
+__kernel void buildMotionMaps(__global const uchar * forwardMotionPtr, int forwardMotion_step, int forwardMotion_offset,
+                              __global const uchar * backwardMotionPtr, int backwardMotion_step, int backwardMotion_offset,
+                              __global const uchar * forwardMapPtr, int forwardMap_step, int forwardMap_offset,
+                              __global const uchar * backwardMapPtr, int backwardMap_step, int backwardMap_offset,
+                              int rows, int cols)
+{
+    int x = get_global_id(0);
+    int y = get_global_id(1);
+
+    if (x < cols && y < rows)
+    {
+        int forwardMotion_index = mad24(forwardMotion_step, y, (int)sizeof(float2) * x + forwardMotion_offset);
+        int backwardMotion_index = mad24(backwardMotion_step, y, (int)sizeof(float2) * x + backwardMotion_offset);
+        int forwardMap_index = mad24(forwardMap_step, y, (int)sizeof(float2) * x + forwardMap_offset);
+        int backwardMap_index = mad24(backwardMap_step, y, (int)sizeof(float2) * x + backwardMap_offset);
+
+        float2 forwardMotion = *(__global const float2 *)(forwardMotionPtr + forwardMotion_index);
+        float2 backwardMotion = *(__global const float2 *)(backwardMotionPtr + backwardMotion_index);
+        __global float2 * forwardMap = (__global float2 *)(forwardMapPtr + forwardMap_index);
+        __global float2 * backwardMap = (__global float2 *)(backwardMapPtr + backwardMap_index);
+
+        float2 basePoint = (float2)(x, y);
+
+        forwardMap[0] = basePoint + backwardMotion;
+        backwardMap[0] = basePoint + forwardMotion;
+    }
+}
+
+__kernel void upscale(__global const uchar * srcptr, int src_step, int src_offset, int src_rows, int src_cols,
+                      __global uchar * dstptr, int dst_step, int dst_offset, int scale)
+{
+    int x = get_global_id(0);
+    int y = get_global_id(1);
+
+    if (x < src_cols && y < src_rows)
+    {
+        int src_index = mad24(y, src_step, sz * x * cn + src_offset);
+        int dst_index = mad24(y * scale, dst_step, sz * x * scale * cn + dst_offset);
+
+        __global const float * src = (__global const float *)(srcptr + src_index);
+        __global float * dst = (__global float *)(dstptr + dst_index);
+
+        #pragma unroll
+        for (int c = 0; c < cn; ++c)
+            dst[c] = src[c];
+    }
+}
+
+
+inline float diffSign1(float a, float b)
+{
+    return a > b ? 1.0f : a < b ? -1.0f : 0.0f;
+}
+
+inline float3 diffSign3(float3 a, float3 b)
+{
+    float3 pos;
+    pos.x = a.x > b.x ? 1.0f : a.x < b.x ? -1.0f : 0.0f;
+    pos.y = a.y > b.y ? 1.0f : a.y < b.y ? -1.0f : 0.0f;
+    pos.z = a.z > b.z ? 1.0f : a.z < b.z ? -1.0f : 0.0f;
+    return pos;
+}
+
+__kernel void diffSign(__global const uchar * src1, int src1_step, int src1_offset,
+                       __global const uchar * src2, int src2_step, int src2_offset,
+                       __global uchar * dst, int dst_step, int dst_offset, int rows, int cols)
+{
+    int x = get_global_id(0);
+    int y = get_global_id(1);
+
+    if (x < cols && y < rows)
+        *(__global float *)(dst + mad24(y, dst_step, sz * x + dst_offset)) =
+            diffSign1(*(__global const float *)(src1 + mad24(y, src1_step, sz * x + src1_offset)),
+                      *(__global const float *)(src2 + mad24(y, src2_step, sz * x + src2_offset)));
+}
+
+__kernel void calcBtvRegularization(__global const uchar * src, int src_step, int src_offset,
+                                    __global uchar * dst, int dst_step, int dst_offset, int dst_rows, int dst_cols,
+                                    int ksize, __constant float * c_btvRegWeights)
+{
+    int x = get_global_id(0) + ksize;
+    int y = get_global_id(1) + ksize;
+
+    if (y < dst_rows - ksize && x < dst_cols - ksize)
+    {
+        src += src_offset;
+
+#if cn == 1
+        const float srcVal = src_elem_at(src, y, src_step, x);
+        float dstVal = 0.0f;
+
+        for (int m = 0, count = 0; m <= ksize; ++m)
+            for (int l = ksize; l + m >= 0; --l, ++count)
+            {
+                dstVal += c_btvRegWeights[count] * (diffSign1(srcVal, src_elem_at(src, y + m, src_step, x + l))
+                    - diffSign1(src_elem_at(src, y - m, src_step, x - l), srcVal));
+            }
+
+        dst_elem_at(dst, y, dst_step, x) = dstVal;
+#elif cn == 3
+        __global const float * src0ptr = (__global const float *)(src + mad24(y, src_step, 3 * sz * x + src_offset));
+        float3 srcVal = (float3)(src0ptr[0], src0ptr[1], src0ptr[2]), dstVal = 0.f;
+
+        for (int m = 0, count = 0; m <= ksize; ++m)
+        {
+            for (int l = ksize; l + m >= 0; --l, ++count)
+            {
+                __global const float * src1ptr = (__global const float *)(src + mad24(y + m, src_step, 3 * sz * (x + l) + src_offset));
+                __global const float * src2ptr = (__global const float *)(src + mad24(y - m, src_step, 3 * sz * (x - l) + src_offset));
+
+                float3 src1 = (float3)(src1ptr[0], src1ptr[1], src1ptr[2]);
+                float3 src2 = (float3)(src2ptr[0], src2ptr[1], src2ptr[2]);
+
+                dstVal += c_btvRegWeights[count] * (diffSign3(srcVal, src1) - diffSign3(src2, srcVal));
+            }
+        }
+
+        __global float * dstptr = (__global float *)(dst + mad24(y, dst_step, 3 * sz * x + dst_offset + 0));
+        dstptr[0] = dstVal.x;
+        dstptr[1] = dstVal.y;
+        dstptr[2] = dstVal.z;
+#else
+#error "Number of channels should be either 1 of 3"
+#endif
+    }
+}

modules/superres/src/optical_flow.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "precomp.hpp"
+#include "opencv2/core/opencl/ocl_defs.hpp"
+
+using namespace cv;
+using namespace cv::cuda;
+using namespace cv::superres;
+using namespace cv::superres::detail;
+
+///////////////////////////////////////////////////////////////////
+// CpuOpticalFlow
+
+namespace
+{
+    class CpuOpticalFlow : public virtual cv::superres::DenseOpticalFlowExt
+    {
+    public:
+        explicit CpuOpticalFlow(int work_type);
+
+        void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2) CV_OVERRIDE;
+        void collectGarbage() CV_OVERRIDE;
+
+    protected:
+        virtual void impl(InputArray input0, InputArray input1, OutputArray dst) = 0;
+
+    private:
+#ifdef HAVE_OPENCL
+        bool ocl_calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2);
+#endif
+
+        int work_type_;
+
+        // Mat
+        Mat buf_[6];
+        Mat flow_;
+        Mat flows_[2];
+
+        // UMat
+        UMat ubuf_[6];
+        UMat uflow_;
+        std::vector<UMat> uflows_;
+    };
+
+    CpuOpticalFlow::CpuOpticalFlow(int work_type) :
+        work_type_(work_type)
+    {
+    }
+
+#ifdef HAVE_OPENCL
+    bool CpuOpticalFlow::ocl_calc(InputArray _frame0, InputArray _frame1, OutputArray _flow1, OutputArray _flow2)
+    {
+        UMat frame0 = arrGetUMat(_frame0, ubuf_[0]);
+        UMat frame1 = arrGetUMat(_frame1, ubuf_[1]);
+
+        CV_Assert( frame1.type() == frame0.type() );
+        CV_Assert( frame1.size() == frame0.size() );
+
+        UMat input0 = convertToType(frame0, work_type_, ubuf_[2], ubuf_[3]);
+        UMat input1 = convertToType(frame1, work_type_, ubuf_[4], ubuf_[5]);
+
+        if (!_flow2.needed())
+        {
+            impl(input0, input1, _flow1);
+            return true;
+        }
+
+        impl(input0, input1, uflow_);
+
+        if (!_flow2.needed())
+            arrCopy(uflow_, _flow1);
+        else
+        {
+            split(uflow_, uflows_);
+
+            arrCopy(uflows_[0], _flow1);
+            arrCopy(uflows_[1], _flow2);
+        }
+
+        return true;
+    }
+#endif
+
+    void CpuOpticalFlow::calc(InputArray _frame0, InputArray _frame1, OutputArray _flow1, OutputArray _flow2)
+    {
+        CV_INSTRUMENT_REGION();
+
+        CV_OCL_RUN(_flow1.isUMat() && (_flow2.isUMat() || !_flow2.needed()),
+                   ocl_calc(_frame0, _frame1, _flow1, _flow2))
+
+        Mat frame0 = arrGetMat(_frame0, buf_[0]);
+        Mat frame1 = arrGetMat(_frame1, buf_[1]);
+
+        CV_Assert( frame1.type() == frame0.type() );
+        CV_Assert( frame1.size() == frame0.size() );
+
+        Mat input0 = convertToType(frame0, work_type_, buf_[2], buf_[3]);
+        Mat input1 = convertToType(frame1, work_type_, buf_[4], buf_[5]);
+
+        if (!_flow2.needed() && _flow1.kind() < _InputArray::OPENGL_BUFFER)
+        {
+            impl(input0, input1, _flow1);
+            return;
+        }
+
+        impl(input0, input1, flow_);
+
+        if (!_flow2.needed())
+            arrCopy(flow_, _flow1);
+        else
+        {
+            split(flow_, flows_);
+
+            arrCopy(flows_[0], _flow1);
+            arrCopy(flows_[1], _flow2);
+        }
+    }
+
+    void CpuOpticalFlow::collectGarbage()
+    {
+        // Mat
+        for (int i = 0; i < 6; ++i)
+            buf_[i].release();
+        flow_.release();
+        flows_[0].release();
+        flows_[1].release();
+
+        // UMat
+        for (int i = 0; i < 6; ++i)
+            ubuf_[i].release();
+        uflow_.release();
+        uflows_[0].release();
+        uflows_[1].release();
+    }
+}
+
+///////////////////////////////////////////////////////////////////
+// Farneback
+
+namespace
+{
+    class Farneback CV_FINAL : public CpuOpticalFlow, public cv::superres::FarnebackOpticalFlow
+    {
+    public:
+        Farneback();
+        void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2) CV_OVERRIDE;
+        void collectGarbage() CV_OVERRIDE;
+
+        inline double getPyrScale() const CV_OVERRIDE { return pyrScale_; }
+        inline void setPyrScale(double val) CV_OVERRIDE { pyrScale_ = val; }
+        inline int getLevelsNumber() const CV_OVERRIDE { return numLevels_; }
+        inline void setLevelsNumber(int val) CV_OVERRIDE { numLevels_ = val; }
+        inline int getWindowSize() const CV_OVERRIDE { return winSize_; }
+        inline void setWindowSize(int val) CV_OVERRIDE { winSize_ = val; }
+        inline int getIterations() const CV_OVERRIDE { return numIters_; }
+        inline void setIterations(int val) CV_OVERRIDE { numIters_ = val; }
+        inline int getPolyN() const CV_OVERRIDE { return polyN_; }
+        inline void setPolyN(int val) CV_OVERRIDE { polyN_ = val; }
+        inline double getPolySigma() const CV_OVERRIDE { return polySigma_; }
+        inline void setPolySigma(double val) CV_OVERRIDE { polySigma_ = val; }
+        inline int getFlags() const CV_OVERRIDE { return flags_; }
+        inline void setFlags(int val) CV_OVERRIDE { flags_ = val; }
+
+    protected:
+        void impl(InputArray input0, InputArray input1, OutputArray dst) CV_OVERRIDE;
+
+    private:
+        double pyrScale_;
+        int numLevels_;
+        int winSize_;
+        int numIters_;
+        int polyN_;
+        double polySigma_;
+        int flags_;
+    };
+
+    Farneback::Farneback() : CpuOpticalFlow(CV_8UC1)
+    {
+        pyrScale_ = 0.5;
+        numLevels_ = 5;
+        winSize_ = 13;
+        numIters_ = 10;
+        polyN_ = 5;
+        polySigma_ = 1.1;
+        flags_ = 0;
+    }
+
+    void Farneback::calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2)
+    {
+        CV_INSTRUMENT_REGION();
+
+        CpuOpticalFlow::calc(frame0, frame1, flow1, flow2);
+    }
+
+    void Farneback::collectGarbage()
+    {
+        CpuOpticalFlow::collectGarbage();
+    }
+
+    void Farneback::impl(InputArray input0, InputArray input1, OutputArray dst)
+    {
+        calcOpticalFlowFarneback(input0, input1, InputOutputArray(dst), pyrScale_,
+                                 numLevels_, winSize_, numIters_,
+                                 polyN_, polySigma_, flags_);
+    }
+}
+
+Ptr<cv::superres::FarnebackOpticalFlow> cv::superres::createOptFlow_Farneback()
+{
+    return makePtr<Farneback>();
+}
+
+///////////////////////////////////////////////////////////////////
+// Simple
+
+/*
+namespace
+{
+    class Simple : public CpuOpticalFlow
+    {
+    public:
+        AlgorithmInfo* info() const;
+
+        Simple();
+
+    protected:
+        void impl(InputArray input0, InputArray input1, OutputArray dst);
+
+    private:
+        int layers_;
+        int averagingBlockSize_;
+        int maxFlow_;
+        double sigmaDist_;
+        double sigmaColor_;
+        int postProcessWindow_;
+        double sigmaDistFix_;
+        double sigmaColorFix_;
+        double occThr_;
+        int upscaleAveragingRadius_;
+        double upscaleSigmaDist_;
+        double upscaleSigmaColor_;
+        double speedUpThr_;
+    };
+
+    CV_INIT_ALGORITHM(Simple, "DenseOpticalFlowExt.Simple",
+                      obj.info()->addParam(obj, "layers", obj.layers_);
+                      obj.info()->addParam(obj, "averagingBlockSize", obj.averagingBlockSize_);
+                      obj.info()->addParam(obj, "maxFlow", obj.maxFlow_);
+                      obj.info()->addParam(obj, "sigmaDist", obj.sigmaDist_);
+                      obj.info()->addParam(obj, "sigmaColor", obj.sigmaColor_);
+                      obj.info()->addParam(obj, "postProcessWindow", obj.postProcessWindow_);
+                      obj.info()->addParam(obj, "sigmaDistFix", obj.sigmaDistFix_);
+                      obj.info()->addParam(obj, "sigmaColorFix", obj.sigmaColorFix_);
+                      obj.info()->addParam(obj, "occThr", obj.occThr_);
+                      obj.info()->addParam(obj, "upscaleAveragingRadius", obj.upscaleAveragingRadius_);
+                      obj.info()->addParam(obj, "upscaleSigmaDist", obj.upscaleSigmaDist_);
+                      obj.info()->addParam(obj, "upscaleSigmaColor", obj.upscaleSigmaColor_);
+                      obj.info()->addParam(obj, "speedUpThr", obj.speedUpThr_))
+
+    Simple::Simple() : CpuOpticalFlow(CV_8UC3)
+    {
+        layers_ = 3;
+        averagingBlockSize_ = 2;
+        maxFlow_ = 4;
+        sigmaDist_ = 4.1;
+        sigmaColor_ = 25.5;
+        postProcessWindow_ = 18;
+        sigmaDistFix_ = 55.0;
+        sigmaColorFix_ = 25.5;
+        occThr_ = 0.35;
+        upscaleAveragingRadius_ = 18;
+        upscaleSigmaDist_ = 55.0;
+        upscaleSigmaColor_ = 25.5;
+        speedUpThr_ = 10;
+    }
+
+    void Simple::impl(InputArray _input0, InputArray _input1, OutputArray _dst)
+    {
+        calcOpticalFlowSF(_input0, _input1, _dst,
+                          layers_,
+                          averagingBlockSize_,
+                          maxFlow_,
+                          sigmaDist_,
+                          sigmaColor_,
+                          postProcessWindow_,
+                          sigmaDistFix_,
+                          sigmaColorFix_,
+                          occThr_,
+                          upscaleAveragingRadius_,
+                          upscaleSigmaDist_,
+                          upscaleSigmaColor_,
+                          speedUpThr_);
+    }
+}
+
+Ptr<DenseOpticalFlowExt> cv::superres::createOptFlow_Simple()
+{
+    return makePtr<Simple>();
+}*/
+
+///////////////////////////////////////////////////////////////////
+// DualTVL1
+
+namespace
+{
+    class DualTVL1 CV_FINAL : public CpuOpticalFlow, public virtual cv::superres::DualTVL1OpticalFlow
+    {
+    public:
+        DualTVL1();
+        void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2) CV_OVERRIDE;
+        void collectGarbage() CV_OVERRIDE;
+
+        inline double getTau() const CV_OVERRIDE { return (*alg_).getTau(); }
+        inline void setTau(double val) CV_OVERRIDE { (*alg_).setTau(val); }
+        inline double getLambda() const CV_OVERRIDE { return (*alg_).getLambda(); }
+        inline void setLambda(double val) CV_OVERRIDE { (*alg_).setLambda(val); }
+        inline double getTheta() const CV_OVERRIDE { return (*alg_).getTheta(); }
+        inline void setTheta(double val) CV_OVERRIDE { (*alg_).setTheta(val); }
+        inline int getScalesNumber() const CV_OVERRIDE { return (*alg_).getScalesNumber(); }
+        inline void setScalesNumber(int val) CV_OVERRIDE { (*alg_).setScalesNumber(val); }
+        inline int getWarpingsNumber() const CV_OVERRIDE { return (*alg_).getWarpingsNumber(); }
+        inline void setWarpingsNumber(int val) CV_OVERRIDE { (*alg_).setWarpingsNumber(val); }
+        inline double getEpsilon() const CV_OVERRIDE { return (*alg_).getEpsilon(); }
+        inline void setEpsilon(double val) CV_OVERRIDE { (*alg_).setEpsilon(val); }
+        inline int  getIterations() const CV_OVERRIDE { return (*alg_).getOuterIterations(); }
+        inline void setIterations(int val) CV_OVERRIDE { (*alg_).setOuterIterations(val); }
+        inline bool getUseInitialFlow() const CV_OVERRIDE { return (*alg_).getUseInitialFlow(); }
+        inline void setUseInitialFlow(bool val) CV_OVERRIDE { (*alg_).setUseInitialFlow(val); }
+
+    protected:
+        void impl(InputArray input0, InputArray input1, OutputArray dst) CV_OVERRIDE;
+
+    private:
+        Ptr<cv::DualTVL1OpticalFlow> alg_;
+    };
+
+    DualTVL1::DualTVL1() : CpuOpticalFlow(CV_8UC1)
+    {
+        alg_ = cv::createOptFlow_DualTVL1();
+    }
+
+    void DualTVL1::calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2)
+    {
+        CV_INSTRUMENT_REGION();
+
+        CpuOpticalFlow::calc(frame0, frame1, flow1, flow2);
+    }
+
+    void DualTVL1::impl(InputArray input0, InputArray input1, OutputArray dst)
+    {
+        alg_->calc(input0, input1, (InputOutputArray)dst);
+    }
+
+    void DualTVL1::collectGarbage()
+    {
+        alg_->collectGarbage();
+        CpuOpticalFlow::collectGarbage();
+    }
+}
+
+Ptr<cv::superres::DualTVL1OpticalFlow> cv::superres::createOptFlow_DualTVL1()
+{
+    return makePtr<DualTVL1>();
+}
+
+///////////////////////////////////////////////////////////////////
+// GpuOpticalFlow
+
+#ifndef HAVE_OPENCV_CUDAOPTFLOW
+
+Ptr<cv::superres::FarnebackOpticalFlow> cv::superres::createOptFlow_Farneback_CUDA()
+{
+    CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform");
+}
+
+Ptr<cv::superres::DualTVL1OpticalFlow> cv::superres::createOptFlow_DualTVL1_CUDA()
+{
+    CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform");
+}
+
+Ptr<cv::superres::BroxOpticalFlow> cv::superres::createOptFlow_Brox_CUDA()
+{
+    CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform");
+}
+
+Ptr<cv::superres::PyrLKOpticalFlow> cv::superres::createOptFlow_PyrLK_CUDA()
+{
+    CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform");
+}
+
+#else // HAVE_OPENCV_CUDAOPTFLOW
+
+namespace
+{
+    class GpuOpticalFlow : public virtual cv::superres::DenseOpticalFlowExt
+    {
+    public:
+        explicit GpuOpticalFlow(int work_type);
+
+        void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2) CV_OVERRIDE;
+        void collectGarbage() CV_OVERRIDE;
+
+    protected:
+        virtual void impl(const GpuMat& input0, const GpuMat& input1, GpuMat& dst1, GpuMat& dst2) = 0;
+
+    private:
+        int work_type_;
+        GpuMat buf_[6];
+        GpuMat u_, v_, flow_;
+    };
+
+    GpuOpticalFlow::GpuOpticalFlow(int work_type) : work_type_(work_type)
+    {
+    }
+
+    void GpuOpticalFlow::calc(InputArray _frame0, InputArray _frame1, OutputArray _flow1, OutputArray _flow2)
+    {
+        CV_INSTRUMENT_REGION();
+
+        GpuMat frame0 = arrGetGpuMat(_frame0, buf_[0]);
+        GpuMat frame1 = arrGetGpuMat(_frame1, buf_[1]);
+
+        CV_Assert( frame1.type() == frame0.type() );
+        CV_Assert( frame1.size() == frame0.size() );
+
+        GpuMat input0 = convertToType(frame0, work_type_, buf_[2], buf_[3]);
+        GpuMat input1 = convertToType(frame1, work_type_, buf_[4], buf_[5]);
+
+        if (_flow2.needed() && _flow1.kind() == _InputArray::CUDA_GPU_MAT && _flow2.kind() == _InputArray::CUDA_GPU_MAT)
+        {
+            impl(input0, input1, _flow1.getGpuMatRef(), _flow2.getGpuMatRef());
+            return;
+        }
+
+        impl(input0, input1, u_, v_);
+
+        if (_flow2.needed())
+        {
+            arrCopy(u_, _flow1);
+            arrCopy(v_, _flow2);
+        }
+        else
+        {
+            GpuMat src[] = {u_, v_};
+            merge(src, 2, flow_);
+            arrCopy(flow_, _flow1);
+        }
+    }
+
+    void GpuOpticalFlow::collectGarbage()
+    {
+        for (int i = 0; i < 6; ++i)
+            buf_[i].release();
+        u_.release();
+        v_.release();
+        flow_.release();
+    }
+}
+
+///////////////////////////////////////////////////////////////////
+// Brox_CUDA
+
+namespace
+{
+    class Brox_CUDA : public GpuOpticalFlow, public virtual cv::superres::BroxOpticalFlow
+    {
+    public:
+        Brox_CUDA();
+        void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2) CV_OVERRIDE;
+        void collectGarbage() CV_OVERRIDE;
+
+        inline double getAlpha() const CV_OVERRIDE { return alpha_; }
+        inline void setAlpha(double val) CV_OVERRIDE { alpha_ = val; }
+        inline double getGamma() const CV_OVERRIDE { return gamma_; }
+        inline void setGamma(double val) CV_OVERRIDE { gamma_ = val; }
+        inline double getScaleFactor() const CV_OVERRIDE { return scaleFactor_; }
+        inline void setScaleFactor(double val) CV_OVERRIDE { scaleFactor_ = val; }
+        inline int getInnerIterations() const CV_OVERRIDE { return innerIterations_; }
+        inline void setInnerIterations(int val) CV_OVERRIDE { innerIterations_ = val; }
+        inline int getOuterIterations() const CV_OVERRIDE { return outerIterations_; }
+        inline void setOuterIterations(int val) CV_OVERRIDE { outerIterations_ = val; }
+        inline int getSolverIterations() const CV_OVERRIDE { return solverIterations_; }
+        inline void setSolverIterations(int val) CV_OVERRIDE { solverIterations_ = val; }
+
+    protected:
+        void impl(const GpuMat& input0, const GpuMat& input1, GpuMat& dst1, GpuMat& dst2) CV_OVERRIDE;
+
+    private:
+        double alpha_;
+        double gamma_;
+        double scaleFactor_;
+        int innerIterations_;
+        int outerIterations_;
+        int solverIterations_;
+
+        Ptr<cuda::BroxOpticalFlow> alg_;
+    };
+
+    Brox_CUDA::Brox_CUDA() : GpuOpticalFlow(CV_32FC1)
+    {
+        alg_ = cuda::BroxOpticalFlow::create(0.197f, 50.0f, 0.8f, 10, 77, 10);
+
+        alpha_ = alg_->getFlowSmoothness();
+        gamma_ = alg_->getGradientConstancyImportance();
+        scaleFactor_ = alg_->getPyramidScaleFactor();
+        innerIterations_ = alg_->getInnerIterations();
+        outerIterations_ = alg_->getOuterIterations();
+        solverIterations_ = alg_->getSolverIterations();
+    }
+
+    void Brox_CUDA::calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2)
+    {
+        GpuOpticalFlow::calc(frame0, frame1, flow1, flow2);
+    }
+
+    void Brox_CUDA::impl(const GpuMat& input0, const GpuMat& input1, GpuMat& dst1, GpuMat& dst2)
+    {
+        alg_->setFlowSmoothness(alpha_);
+        alg_->setGradientConstancyImportance(gamma_);
+        alg_->setPyramidScaleFactor(scaleFactor_);
+        alg_->setInnerIterations(innerIterations_);
+        alg_->setOuterIterations(outerIterations_);
+        alg_->setSolverIterations(solverIterations_);
+
+        GpuMat flow;
+        alg_->calc(input0, input1, flow);
+
+        GpuMat flows[2];
+        cuda::split(flow, flows);
+
+        dst1 = flows[0];
+        dst2 = flows[1];
+    }
+
+    void Brox_CUDA::collectGarbage()
+    {
+        alg_ = cuda::BroxOpticalFlow::create(alpha_, gamma_, scaleFactor_, innerIterations_, outerIterations_, solverIterations_);
+        GpuOpticalFlow::collectGarbage();
+    }
+}
+
+Ptr<cv::superres::BroxOpticalFlow> cv::superres::createOptFlow_Brox_CUDA()
+{
+    return makePtr<Brox_CUDA>();
+}
+
+///////////////////////////////////////////////////////////////////
+// PyrLK_CUDA
+
+namespace
+{
+    class PyrLK_CUDA : public GpuOpticalFlow, public cv::superres::PyrLKOpticalFlow
+    {
+    public:
+        PyrLK_CUDA();
+        void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2) CV_OVERRIDE;
+        void collectGarbage() CV_OVERRIDE;
+
+        inline int getWindowSize() const CV_OVERRIDE { return winSize_; }
+        inline void setWindowSize(int val) CV_OVERRIDE { winSize_ = val; }
+        inline int getMaxLevel() const CV_OVERRIDE { return maxLevel_; }
+        inline void setMaxLevel(int val) CV_OVERRIDE { maxLevel_ = val; }
+        inline int getIterations() const CV_OVERRIDE { return iterations_; }
+        inline void setIterations(int val) CV_OVERRIDE { iterations_ = val; }
+
+    protected:
+        void impl(const GpuMat& input0, const GpuMat& input1, GpuMat& dst1, GpuMat& dst2) CV_OVERRIDE;
+
+    private:
+        int winSize_;
+        int maxLevel_;
+        int iterations_;
+
+        Ptr<cuda::DensePyrLKOpticalFlow> alg_;
+    };
+
+    PyrLK_CUDA::PyrLK_CUDA() : GpuOpticalFlow(CV_8UC1)
+    {
+        alg_ = cuda::DensePyrLKOpticalFlow::create();
+
+        winSize_ = alg_->getWinSize().width;
+        maxLevel_ = alg_->getMaxLevel();
+        iterations_ = alg_->getNumIters();
+    }
+
+    void PyrLK_CUDA::calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2)
+    {
+        GpuOpticalFlow::calc(frame0, frame1, flow1, flow2);
+    }
+
+    void PyrLK_CUDA::impl(const GpuMat& input0, const GpuMat& input1, GpuMat& dst1, GpuMat& dst2)
+    {
+        alg_->setWinSize(Size(winSize_, winSize_));
+        alg_->setMaxLevel(maxLevel_);
+        alg_->setNumIters(iterations_);
+
+        GpuMat flow;
+        alg_->calc(input0, input1, flow);
+
+        GpuMat flows[2];
+        cuda::split(flow, flows);
+
+        dst1 = flows[0];
+        dst2 = flows[1];
+    }
+
+    void PyrLK_CUDA::collectGarbage()
+    {
+        alg_ = cuda::DensePyrLKOpticalFlow::create();
+        GpuOpticalFlow::collectGarbage();
+    }
+}
+
+Ptr<cv::superres::PyrLKOpticalFlow> cv::superres::createOptFlow_PyrLK_CUDA()
+{
+    return makePtr<PyrLK_CUDA>();
+}
+
+///////////////////////////////////////////////////////////////////
+// Farneback_CUDA
+
+namespace
+{
+    class Farneback_CUDA : public GpuOpticalFlow, public cv::superres::FarnebackOpticalFlow
+    {
+    public:
+        Farneback_CUDA();
+        void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2) CV_OVERRIDE;
+        void collectGarbage() CV_OVERRIDE;
+
+        inline double getPyrScale() const CV_OVERRIDE { return pyrScale_; }
+        inline void setPyrScale(double val) CV_OVERRIDE { pyrScale_ = val; }
+        inline int getLevelsNumber() const CV_OVERRIDE { return numLevels_; }
+        inline void setLevelsNumber(int val) CV_OVERRIDE { numLevels_ = val; }
+        inline int getWindowSize() const CV_OVERRIDE { return winSize_; }
+        inline void setWindowSize(int val) CV_OVERRIDE { winSize_ = val; }
+        inline int getIterations() const CV_OVERRIDE { return numIters_; }
+        inline void setIterations(int val) CV_OVERRIDE { numIters_ = val; }
+        inline int getPolyN() const CV_OVERRIDE { return polyN_; }
+        inline void setPolyN(int val) CV_OVERRIDE { polyN_ = val; }
+        inline double getPolySigma() const CV_OVERRIDE { return polySigma_; }
+        inline void setPolySigma(double val) CV_OVERRIDE { polySigma_ = val; }
+        inline int getFlags() const CV_OVERRIDE { return flags_; }
+        inline void setFlags(int val) CV_OVERRIDE { flags_ = val; }
+
+    protected:
+        void impl(const GpuMat& input0, const GpuMat& input1, GpuMat& dst1, GpuMat& dst2) CV_OVERRIDE;
+
+    private:
+        double pyrScale_;
+        int numLevels_;
+        int winSize_;
+        int numIters_;
+        int polyN_;
+        double polySigma_;
+        int flags_;
+
+        Ptr<cuda::FarnebackOpticalFlow> alg_;
+    };
+
+    Farneback_CUDA::Farneback_CUDA() : GpuOpticalFlow(CV_8UC1)
+    {
+        alg_ = cuda::FarnebackOpticalFlow::create();
+
+        pyrScale_ = alg_->getPyrScale();
+        numLevels_ = alg_->getNumLevels();
+        winSize_ = alg_->getWinSize();
+        numIters_ = alg_->getNumIters();
+        polyN_ = alg_->getPolyN();
+        polySigma_ = alg_->getPolySigma();
+        flags_ = alg_->getFlags();
+    }
+
+    void Farneback_CUDA::calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2)
+    {
+        GpuOpticalFlow::calc(frame0, frame1, flow1, flow2);
+    }
+
+    void Farneback_CUDA::impl(const GpuMat& input0, const GpuMat& input1, GpuMat& dst1, GpuMat& dst2)
+    {
+        alg_->setPyrScale(pyrScale_);
+        alg_->setNumLevels(numLevels_);
+        alg_->setWinSize(winSize_);
+        alg_->setNumIters(numIters_);
+        alg_->setPolyN(polyN_);
+        alg_->setPolySigma(polySigma_);
+        alg_->setFlags(flags_);
+
+        GpuMat flow;
+        alg_->calc(input0, input1, flow);
+
+        GpuMat flows[2];
+        cuda::split(flow, flows);
+
+        dst1 = flows[0];
+        dst2 = flows[1];
+    }
+
+    void Farneback_CUDA::collectGarbage()
+    {
+        alg_ = cuda::FarnebackOpticalFlow::create();
+        GpuOpticalFlow::collectGarbage();
+    }
+}
+
+Ptr<cv::superres::FarnebackOpticalFlow> cv::superres::createOptFlow_Farneback_CUDA()
+{
+    return makePtr<Farneback_CUDA>();
+}
+
+///////////////////////////////////////////////////////////////////
+// DualTVL1_CUDA
+
+namespace
+{
+    class DualTVL1_CUDA : public GpuOpticalFlow, public cv::superres::DualTVL1OpticalFlow
+    {
+    public:
+        DualTVL1_CUDA();
+        void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2) CV_OVERRIDE;
+        void collectGarbage() CV_OVERRIDE;
+
+        inline double getTau() const CV_OVERRIDE { return tau_; }
+        inline void setTau(double val) CV_OVERRIDE { tau_ = val; }
+        inline double getLambda() const CV_OVERRIDE { return lambda_; }
+        inline void setLambda(double val) CV_OVERRIDE { lambda_ = val; }
+        inline double getTheta() const CV_OVERRIDE { return theta_; }
+        inline void setTheta(double val) CV_OVERRIDE { theta_ = val; }
+        inline int getScalesNumber() const CV_OVERRIDE { return nscales_; }
+        inline void setScalesNumber(int val) CV_OVERRIDE { nscales_ = val; }
+        inline int getWarpingsNumber() const CV_OVERRIDE { return warps_; }
+        inline void setWarpingsNumber(int val) CV_OVERRIDE { warps_ = val; }
+        inline double getEpsilon() const CV_OVERRIDE { return epsilon_; }
+        inline void setEpsilon(double val) CV_OVERRIDE { epsilon_ = val; }
+        inline int getIterations() const CV_OVERRIDE { return iterations_; }
+        inline void setIterations(int val) CV_OVERRIDE { iterations_ = val; }
+        inline bool getUseInitialFlow() const CV_OVERRIDE { return useInitialFlow_; }
+        inline void setUseInitialFlow(bool val) CV_OVERRIDE { useInitialFlow_ = val; }
+
+    protected:
+        void impl(const GpuMat& input0, const GpuMat& input1, GpuMat& dst1, GpuMat& dst2) CV_OVERRIDE;
+
+    private:
+        double tau_;
+        double lambda_;
+        double theta_;
+        int nscales_;
+        int warps_;
+        double epsilon_;
+        int iterations_;
+        bool useInitialFlow_;
+
+        Ptr<cuda::OpticalFlowDual_TVL1> alg_;
+    };
+
+    DualTVL1_CUDA::DualTVL1_CUDA() : GpuOpticalFlow(CV_8UC1)
+    {
+        alg_ = cuda::OpticalFlowDual_TVL1::create();
+
+        tau_ = alg_->getTau();
+        lambda_ = alg_->getLambda();
+        theta_ = alg_->getTheta();
+        nscales_ = alg_->getNumScales();
+        warps_ = alg_->getNumWarps();
+        epsilon_ = alg_->getEpsilon();
+        iterations_ = alg_->getNumIterations();
+        useInitialFlow_ = alg_->getUseInitialFlow();
+    }
+
+    void DualTVL1_CUDA::calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2)
+    {
+        GpuOpticalFlow::calc(frame0, frame1, flow1, flow2);
+    }
+
+    void DualTVL1_CUDA::impl(const GpuMat& input0, const GpuMat& input1, GpuMat& dst1, GpuMat& dst2)
+    {
+        alg_->setTau(tau_);
+        alg_->setLambda(lambda_);
+        alg_->setTheta(theta_);
+        alg_->setNumScales(nscales_);
+        alg_->setNumWarps(warps_);
+        alg_->setEpsilon(epsilon_);
+        alg_->setNumIterations(iterations_);
+        alg_->setUseInitialFlow(useInitialFlow_);
+
+        GpuMat flow;
+        alg_->calc(input0, input1, flow);
+
+        GpuMat flows[2];
+        cuda::split(flow, flows);
+
+        dst1 = flows[0];
+        dst2 = flows[1];
+    }
+
+    void DualTVL1_CUDA::collectGarbage()
+    {
+        alg_ = cuda::OpticalFlowDual_TVL1::create();
+        GpuOpticalFlow::collectGarbage();
+    }
+}
+
+Ptr<cv::superres::DualTVL1OpticalFlow> cv::superres::createOptFlow_DualTVL1_CUDA()
+{
+    return makePtr<DualTVL1_CUDA>();
+}
+
+#endif // HAVE_OPENCV_CUDAOPTFLOW

modules/superres/src/precomp.hpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef __OPENCV_PRECOMP_H__
+#define __OPENCV_PRECOMP_H__
+
+#include <vector>
+#include <limits>
+
+#include "opencv2/opencv_modules.hpp"
+#include "opencv2/core.hpp"
+#include "opencv2/core/cuda.hpp"
+#include "opencv2/core/opengl.hpp"
+#include "opencv2/core/utility.hpp"
+#include "opencv2/imgproc.hpp"
+#include "opencv2/video/tracking.hpp"
+#include "opencv2/core/private.hpp"
+
+#include "opencv2/core/private.cuda.hpp"
+#include "opencv2/core/ocl.hpp"
+
+#ifdef HAVE_OPENCV_CUDAARITHM
+#  include "opencv2/cudaarithm.hpp"
+#endif
+
+#ifdef HAVE_OPENCV_CUDAWARPING
+#  include "opencv2/cudawarping.hpp"
+#endif
+
+#ifdef HAVE_OPENCV_CUDAFILTERS
+#  include "opencv2/cudafilters.hpp"
+#endif
+
+#ifdef HAVE_OPENCV_CUDAIMGPROC
+#  include "opencv2/cudaimgproc.hpp"
+#endif
+
+#ifdef HAVE_OPENCV_CUDAOPTFLOW
+#  include "opencv2/cudaoptflow.hpp"
+#endif
+
+#ifdef HAVE_OPENCV_CUDACODEC
+#  include "opencv2/cudacodec.hpp"
+#endif
+
+#ifdef HAVE_OPENCV_VIDEOIO
+    #include "opencv2/videoio.hpp"
+#endif
+
+#include "opencv2/superres.hpp"
+#include "opencv2/superres/optical_flow.hpp"
+#include "input_array_utility.hpp"
+
+#include "ring_buffer.hpp"
+
+#include "opencv2/core/private.hpp"
+
+#endif /* __OPENCV_PRECOMP_H__ */

modules/superres/src/ring_buffer.hpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef __RING_BUFFER_HPP__
+#define __RING_BUFFER_HPP__
+
+#include "precomp.hpp"
+
+namespace cv
+{
+    namespace superres
+    {
+        namespace detail
+        {
+            template <typename T, class A>
+            inline const T& at(int index, const std::vector<T, A>& items)
+            {
+                const int len = static_cast<int>(items.size());
+                if (index < 0)
+                    index -= ((index - len + 1) / len) * len;
+                if (index >= len)
+                    index %= len;
+                return items[index];
+            }
+
+            template <typename T, class A>
+            inline T& at(int index, std::vector<T, A>& items)
+            {
+                const int len = static_cast<int>(items.size());
+                if (index < 0)
+                    index -= ((index - len + 1) / len) * len;
+                if (index >= len)
+                    index %= len;
+                return items[index];
+            }
+        }
+    }
+}
+
+#endif // __RING_BUFFER_HPP__

modules/superres/src/super_resolution.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "precomp.hpp"
+
+using namespace cv;
+using namespace cv::superres;
+
+cv::superres::SuperResolution::SuperResolution()
+{
+    frameSource_ = createFrameSource_Empty();
+    firstCall_ = true;
+    isUmat_ = false;
+}
+
+void cv::superres::SuperResolution::setInput(const Ptr<FrameSource>& frameSource)
+{
+    frameSource_ = frameSource;
+    firstCall_ = true;
+    isUmat_ = false;
+}
+
+void cv::superres::SuperResolution::nextFrame(OutputArray frame)
+{
+    CV_INSTRUMENT_REGION();
+
+    isUmat_ = frame.isUMat();
+
+    if (firstCall_)
+    {
+        initImpl(frameSource_);
+        firstCall_ = false;
+    }
+
+    processImpl(frameSource_, frame);
+}
+
+void cv::superres::SuperResolution::reset()
+{
+    frameSource_->reset();
+    firstCall_ = true;
+    isUmat_ = false;
+}
+
+void cv::superres::SuperResolution::collectGarbage()
+{
+}

modules/superres/test/test_main.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "test_precomp.hpp"
+
+#if defined(HAVE_HPX)
+    #include <hpx/hpx_main.hpp>
+#endif
+
+CV_TEST_MAIN("superres")

modules/superres/test/test_precomp.hpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+#ifndef __OPENCV_TEST_PRECOMP_HPP__
+#define __OPENCV_TEST_PRECOMP_HPP__
+
+#include "opencv2/ts.hpp"
+#include "opencv2/superres.hpp"
+
+#endif

modules/superres/test/test_superres.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "test_precomp.hpp"
+#include "cvconfig.h"
+#include "../src/input_array_utility.hpp"
+#include "opencv2/ts/ocl_test.hpp"
+
+namespace opencv_test {
+
+#ifdef HAVE_VIDEO_INPUT
+
+namespace {
+
+class AllignedFrameSource : public cv::superres::FrameSource
+{
+public:
+    AllignedFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale);
+
+    void nextFrame(cv::OutputArray frame);
+    void reset();
+
+private:
+    cv::Ptr<cv::superres::FrameSource> base_;
+
+    cv::Mat origFrame_;
+    int scale_;
+};
+
+AllignedFrameSource::AllignedFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale) :
+    base_(base), scale_(scale)
+{
+    CV_Assert( base_ );
+}
+
+void AllignedFrameSource::nextFrame(cv::OutputArray frame)
+{
+    base_->nextFrame(origFrame_);
+
+    if (origFrame_.rows % scale_ == 0 && origFrame_.cols % scale_ == 0)
+        cv::superres::arrCopy(origFrame_, frame);
+    else
+    {
+        cv::Rect ROI(0, 0, (origFrame_.cols / scale_) * scale_, (origFrame_.rows / scale_) * scale_);
+        cv::superres::arrCopy(origFrame_(ROI), frame);
+    }
+}
+
+void AllignedFrameSource::reset()
+{
+    base_->reset();
+}
+
+class DegradeFrameSource : public cv::superres::FrameSource
+{
+public:
+    DegradeFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale);
+
+    void nextFrame(cv::OutputArray frame);
+    void reset();
+
+private:
+    cv::Ptr<cv::superres::FrameSource> base_;
+
+    cv::Mat origFrame_;
+    cv::Mat blurred_;
+    cv::Mat deg_;
+    double iscale_;
+};
+
+DegradeFrameSource::DegradeFrameSource(const cv::Ptr<cv::superres::FrameSource>& base, int scale) :
+    base_(base), iscale_(1.0 / scale)
+{
+    CV_Assert( base_ );
+}
+
+static void addGaussNoise(cv::OutputArray _image, double sigma)
+{
+    int type = _image.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
+    cv::Mat noise(_image.size(), CV_32FC(cn));
+    cvtest::TS::ptr()->get_rng().fill(noise, cv::RNG::NORMAL, 0.0, sigma);
+
+    cv::addWeighted(_image, 1.0, noise, 1.0, 0.0, _image, depth);
+}
+
+static void addSpikeNoise(cv::OutputArray _image, int frequency)
+{
+    cv::Mat_<uchar> mask(_image.size(), 0);
+
+    for (int y = 0; y < mask.rows; ++y)
+        for (int x = 0; x < mask.cols; ++x)
+            if (cvtest::TS::ptr()->get_rng().uniform(0, frequency) < 1)
+                mask(y, x) = 255;
+
+    _image.setTo(cv::Scalar::all(255), mask);
+}
+
+void DegradeFrameSource::nextFrame(cv::OutputArray frame)
+{
+    base_->nextFrame(origFrame_);
+
+    cv::GaussianBlur(origFrame_, blurred_, cv::Size(5, 5), 0);
+    cv::resize(blurred_, deg_, cv::Size(), iscale_, iscale_, cv::INTER_NEAREST);
+
+    addGaussNoise(deg_, 10.0);
+    addSpikeNoise(deg_, 500);
+
+    cv::superres::arrCopy(deg_, frame);
+}
+
+void DegradeFrameSource::reset()
+{
+    base_->reset();
+}
+
+double MSSIM(cv::InputArray _i1, cv::InputArray _i2)
+{
+    const double C1 = 6.5025;
+    const double C2 = 58.5225;
+
+    const int depth = CV_32F;
+
+    cv::Mat I1, I2;
+    _i1.getMat().convertTo(I1, depth);
+    _i2.getMat().convertTo(I2, depth);
+
+    cv::Mat I2_2  = I2.mul(I2); // I2^2
+    cv::Mat I1_2  = I1.mul(I1); // I1^2
+    cv::Mat I1_I2 = I1.mul(I2); // I1 * I2
+
+    cv::Mat mu1, mu2;
+    cv::GaussianBlur(I1, mu1, cv::Size(11, 11), 1.5);
+    cv::GaussianBlur(I2, mu2, cv::Size(11, 11), 1.5);
+
+    cv::Mat mu1_2   = mu1.mul(mu1);
+    cv::Mat mu2_2   = mu2.mul(mu2);
+    cv::Mat mu1_mu2 = mu1.mul(mu2);
+
+    cv::Mat sigma1_2, sigma2_2, sigma12;
+
+    cv::GaussianBlur(I1_2, sigma1_2, cv::Size(11, 11), 1.5);
+    sigma1_2 -= mu1_2;
+
+    cv::GaussianBlur(I2_2, sigma2_2, cv::Size(11, 11), 1.5);
+    sigma2_2 -= mu2_2;
+
+    cv::GaussianBlur(I1_I2, sigma12, cv::Size(11, 11), 1.5);
+    sigma12 -= mu1_mu2;
+
+    cv::Mat t1, t2;
+    cv::Mat numerator;
+    cv::Mat denominator;
+
+    // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
+    t1 = 2 * mu1_mu2 + C1;
+    t2 = 2 * sigma12 + C2;
+    numerator = t1.mul(t2);
+
+    // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
+    t1 = mu1_2 + mu2_2 + C1;
+    t2 = sigma1_2 + sigma2_2 + C2;
+    denominator = t1.mul(t2);
+
+    // ssim_map =  numerator./denominator;
+    cv::Mat ssim_map;
+    cv::divide(numerator, denominator, ssim_map);
+
+    // mssim = average of ssim map
+    cv::Scalar mssim = cv::mean(ssim_map);
+
+    if (_i1.channels() == 1)
+        return mssim[0];
+
+    return (mssim[0] + mssim[1] + mssim[3]) / 3;
+}
+
+class SuperResolution : public testing::Test
+{
+public:
+    template <typename T>
+    void RunTest(cv::Ptr<cv::superres::SuperResolution> superRes);
+};
+
+template <typename T>
+void SuperResolution::RunTest(cv::Ptr<cv::superres::SuperResolution> superRes)
+{
+    const std::string inputVideoName = cvtest::TS::ptr()->get_data_path() + "car.avi";
+    const int scale = 2;
+    const int iterations = 100;
+    const int temporalAreaRadius = 2;
+
+    ASSERT_FALSE( superRes.empty() );
+
+    const int btvKernelSize = superRes->getKernelSize();
+
+    superRes->setScale(scale);
+    superRes->setIterations(iterations);
+    superRes->setTemporalAreaRadius(temporalAreaRadius);
+
+    cv::Ptr<cv::superres::FrameSource> goldSource(new AllignedFrameSource(cv::superres::createFrameSource_Video(inputVideoName), scale));
+    cv::Ptr<cv::superres::FrameSource> lowResSource(new DegradeFrameSource(
+        cv::makePtr<AllignedFrameSource>(cv::superres::createFrameSource_Video(inputVideoName), scale), scale));
+
+    // skip first frame
+    cv::Mat frame;
+
+    lowResSource->nextFrame(frame);
+    goldSource->nextFrame(frame);
+
+    cv::Rect inner(btvKernelSize, btvKernelSize, frame.cols - 2 * btvKernelSize, frame.rows - 2 * btvKernelSize);
+
+    superRes->setInput(lowResSource);
+
+    double srAvgMSSIM = 0.0;
+    const int count = 10;
+
+    cv::Mat goldFrame;
+    T superResFrame;
+    for (int i = 0; i < count; ++i)
+    {
+        goldSource->nextFrame(goldFrame);
+        ASSERT_FALSE( goldFrame.empty() );
+
+        superRes->nextFrame(superResFrame);
+        ASSERT_FALSE( superResFrame.empty() );
+
+        const double srMSSIM = MSSIM(goldFrame(inner), superResFrame);
+
+        srAvgMSSIM += srMSSIM;
+    }
+
+    srAvgMSSIM /= count;
+
+    EXPECT_GE( srAvgMSSIM, 0.5 );
+}
+
+TEST_F(SuperResolution, BTVL1)
+{
+    RunTest<cv::Mat>(cv::superres::createSuperResolution_BTVL1());
+}
+
+#if defined(HAVE_CUDA) && defined(HAVE_OPENCV_CUDAARITHM) && defined(HAVE_OPENCV_CUDAWARPING) && defined(HAVE_OPENCV_CUDAFILTERS)
+
+TEST_F(SuperResolution, BTVL1_CUDA)
+{
+    RunTest<cv::Mat>(cv::superres::createSuperResolution_BTVL1_CUDA());
+}
+
+#endif
+
+} // namespace
+
+#ifdef HAVE_OPENCL
+
+namespace ocl {
+
+OCL_TEST_F(SuperResolution, BTVL1)
+{
+    RunTest<cv::UMat>(cv::superres::createSuperResolution_BTVL1());
+}
+
+} // namespace opencv_test::ocl
+
+#endif
+
+#endif // HAVE_VIDEO_INPUT
+
+} // namespace