added DisparityBilateralFilter to gpu module

modules/gpu/include/opencv2/gpu/gpu.hpp

@@ -391,6 +391,7 @@ namespace cv
         ////////////////////////// StereoBeliefPropagation ///////////////////////////
         // "Efficient Belief Propagation for Early Vision" 
         // P.Felzenszwalb
+
         class CV_EXPORTS StereoBeliefPropagation
         {
         public:
@@ -504,6 +505,45 @@ namespace cv
 
             GpuMat out;
         };
+
+        /////////////////////////// DisparityBilateralFilter ///////////////////////////
+        // Disparity map refinement using joint bilateral filtering given a single color image.
+        // Qingxiong Yang, Liang Wang†, Narendra Ahuja         
+        // http://vision.ai.uiuc.edu/~qyang6/
+
+        class CV_EXPORTS DisparityBilateralFilter
+        {
+        public:
+            enum { DEFAULT_NDISP  = 64 };
+            enum { DEFAULT_RADIUS = 3 };
+            enum { DEFAULT_ITERS  = 1 };
+
+            //! the default constructor
+            explicit DisparityBilateralFilter(int ndisp = DEFAULT_NDISP, int radius = DEFAULT_RADIUS, int iters = DEFAULT_ITERS);
+
+            //! the full constructor taking the number of disparities, filter radius,
+            //! number of iterations, truncation of data continuity, truncation of disparity continuity
+            //! and filter range sigma
+            DisparityBilateralFilter(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold, float sigma_range);
+
+            //! the disparity map refinement operator. Refine disparity map using joint bilateral filtering given a single color image.
+            //! disparity must have CV_8U or CV_16S type, image must have CV_8UC1 or CV_8UC3 type.
+            void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst);
+
+            //! Acync version
+            void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream);
+
+            int ndisp;
+            int radius;
+            int iters;
+
+            float edge_threshold;
+            float max_disc_threshold;
+            float sigma_range;
+        private:
+            std::vector<float> table_color;
+            GpuMat table_space;
+        };
     }
 
     //! Speckle filtering - filters small connected components on diparity image.

modules/gpu/src/bilateral_filter.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 GpuMaterials 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::gpu;
+using namespace std;
+
+#if !defined (HAVE_CUDA)
+
+cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int, int, int) { throw_nogpu(); }
+cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int, int, int, float, float, float) { throw_nogpu(); }
+
+void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
+void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
+
+#else /* !defined (HAVE_CUDA) */
+
+namespace cv { namespace gpu { namespace bf 
+{
+    void calc_space_weighted_filter_gpu(const DevMem2Df& table_space, int half, float dist_space, cudaStream_t stream);
+    void load_constants(float* table_color, const DevMem2Df& table_space, int ndisp, int radius, short edge_disc, short max_disc);
+
+    void bilateral_filter_gpu(const DevMem2D& disp, const DevMem2D& img, int channels, int iters, cudaStream_t stream);
+    void bilateral_filter_gpu(const DevMem2D_<short>& disp, const DevMem2D& img, int channels, int iters, cudaStream_t stream);
+}}}
+
+namespace
+{
+    const float DEFAULT_EDGE_THRESHOLD = 0.1f;
+    const float DEFAULT_MAX_DISC_THRESHOLD = 0.2f;
+    const float DEFAULT_SIGMA_RANGE = 10.0f;
+
+    inline void calc_color_weighted_table(vector<float>& table_color, float sigma_range, int len)
+    {
+        float* color_table_x;
+        
+        table_color.resize(len);
+        color_table_x = &table_color[0];
+
+        for(int y = 0; y < len; y++) 
+            table_color[y] = static_cast<float>(std::exp(-double(y * y) / (2 * sigma_range * sigma_range)));
+    }
+
+    inline void calc_space_weighted_filter(GpuMat& table_space, int win_size, float dist_space, cudaStream_t stream)
+    {
+        int half = (win_size >> 1);
+        table_space.create(half + 1, half + 1, CV_32F);
+
+        bf::calc_space_weighted_filter_gpu(table_space, half, dist_space, stream);
+    }
+
+    template <typename T>
+    void bilateral_filter_operator(DisparityBilateralFilter& rthis, vector<float>& table_color, GpuMat& table_space, 
+                                   const GpuMat& disp, const GpuMat& img, GpuMat& dst, cudaStream_t stream)
+    {
+        calc_color_weighted_table(table_color, rthis.sigma_range, 255);
+        calc_space_weighted_filter(table_space, rthis.radius * 2 + 1, rthis.radius + 1.0f, stream);
+
+        short edge_disc = max<short>(short(1), short(rthis.ndisp * rthis.edge_threshold + 0.5));
+        short max_disc = short(rthis.ndisp * rthis.max_disc_threshold + 0.5);
+
+        bf::load_constants(&table_color[0], table_space, rthis.ndisp, rthis.radius, edge_disc, max_disc);
+
+        if (&dst != &disp)
+            disp.copyTo(dst);
+
+        bf::bilateral_filter_gpu((DevMem2D_<T>)dst, img, img.channels(), rthis.iters, stream);
+    }
+
+    typedef void (*bilateral_filter_operator_t)(DisparityBilateralFilter& rthis, vector<float>& table_color, GpuMat& table_space, 
+                                   const GpuMat& disp, const GpuMat& img, GpuMat& dst, cudaStream_t stream);
+    
+    const bilateral_filter_operator_t operators[] = 
+        {bilateral_filter_operator<unsigned char>, 0, 0, bilateral_filter_operator<short>, 0, 0, 0, 0};
+}
+
+cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp_, int radius_, int iters_)
+    : ndisp(ndisp_), radius(radius_), iters(iters_), edge_threshold(DEFAULT_EDGE_THRESHOLD), max_disc_threshold(DEFAULT_MAX_DISC_THRESHOLD),
+      sigma_range(DEFAULT_SIGMA_RANGE)
+{
+}
+
+cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp_, int radius_, int iters_, float edge_threshold_, 
+                                                     float max_disc_threshold_, float sigma_range_)
+    : ndisp(ndisp_), radius(radius_), iters(iters_), edge_threshold(edge_threshold_), max_disc_threshold(max_disc_threshold_), 
+      sigma_range(sigma_range_)
+{
+}
+
+void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat& disp, const GpuMat& img, GpuMat& dst)
+{
+    CV_DbgAssert(0 < ndisp && 0 < radius && 0 < iters);
+    CV_Assert(disp.rows == img.rows && disp.cols == img.cols && (disp.type() == CV_8U || disp.type() == CV_16S) && (img.type() == CV_8UC1 || img.type() == CV_8UC3));
+    operators[disp.type()](*this, table_color, table_space, disp, img, dst, 0);
+}
+
+void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat& disp, const GpuMat& img, GpuMat& dst, Stream& stream)
+{
+    CV_DbgAssert(0 < ndisp && 0 < radius && 0 < iters);
+    CV_Assert(disp.rows == img.rows && disp.cols == img.cols && (disp.type() == CV_8U || disp.type() == CV_16S) && (img.type() == CV_8UC1 || img.type() == CV_8UC3));
+    operators[disp.type()](*this, table_color, table_space, disp, img, dst, StreamAccessor::getStream(stream));
+}
+
+#endif /* !defined (HAVE_CUDA) */