Merge pull request #375 from zhou-chao:wmfv3

modules/ximgproc/doc/ximgproc.bib

@@ -148,3 +148,21 @@
   month = {June},
   year = {2015}
 }
+
+@incollection{zhang2014rolling,
+  title={Rolling guidance filter},
+  author={Zhang, Qi and Shen, Xiaoyong and Xu, Li and Jia, Jiaya},
+  booktitle={Computer Vision--ECCV 2014},
+  pages={815--830},
+  year={2014},
+  publisher={Springer}
+}
+
+@inproceedings{zhang2014100+,
+  title={100+ times faster weighted median filter (WMF)},
+  author={Zhang, Qi and Xu, Li and Jia, Jiaya},
+  booktitle={Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on},
+  pages={2830--2837},
+  year={2014},
+  organization={IEEE}
+}

modules/ximgproc/include/opencv2/ximgproc.hpp

@@ -45,6 +45,7 @@
 #include "ximgproc/segmentation.hpp"
 #include "ximgproc/fast_hough_transform.hpp"
 #include "ximgproc/estimated_covariance.hpp"
+#include "ximgproc/weighted_median_filter.hpp"
 #include "ximgproc/slic.hpp"
 #include "ximgproc/lsc.hpp"
 

modules/ximgproc/include/opencv2/ximgproc/edge_filter.hpp

@@ -321,6 +321,8 @@ void jointBilateralFilter(InputArray joint, InputArray src, OutputArray dst, int
 
 /** @brief Applies the rolling guidance filter to an image.
 
+For more details, please see @cite zhang2014rolling
+
 @param src Source 8-bit or floating-point, 1-channel or 3-channel image.
 
 @param dst Destination image of the same size and type as src.

modules/ximgproc/include/opencv2/ximgproc/weighted_median_filter.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) 2015, The Chinese University of Hong Kong, 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_WEIGHTED_MEDIAN_FILTER_HPP__
+#define  __OPENCV_WEIGHTED_MEDIAN_FILTER_HPP__
+#ifdef __cplusplus
+
+/**
+* @file
+* @date Sept 9, 2015
+* @author Zhou Chao
+*/
+
+#include <opencv2/core.hpp>
+#include <string>
+
+namespace cv
+{
+namespace ximgproc
+{
+
+/**
+* @brief Specifies weight types of weighted median filter.
+*/
+enum WMFWeightType
+{
+    WMF_EXP, //!< \f$exp(-|I1-I2|^2/(2*sigma^2))\f$
+    WMF_IV1, //!< \f$(|I1-I2|+sigma)^-1\f$
+    WMF_IV2, //!< \f$(|I1-I2|^2+sigma^2)^-1\f$
+    WMF_COS, //!< \f$dot(I1,I2)/(|I1|*|I2|)\f$
+    WMF_JAC, //!< \f$(min(r1,r2)+min(g1,g2)+min(b1,b2))/(max(r1,r2)+max(g1,g2)+max(b1,b2))\f$
+    WMF_OFF //!< unweighted
+};
+
+/**
+* @brief   Applies weighted median filter to an image.
+*
+* For more details about this implementation, please see @cite zhang2014100+
+*
+* @param   joint       Joint 8-bit, 1-channel or 3-channel image.
+* @param   src         Source 8-bit or floating-point, 1-channel or 3-channel image.
+* @param   dst         Destination image.
+* @param   r           Radius of filtering kernel, should be a positive integer.
+* @param   sigma       Filter range standard deviation for the joint image.
+* @param   weightType  weightType The type of weight definition, see WMFWeightType
+* @param   mask        A 0-1 mask that has the same size with I. This mask is used to ignore the effect of some pixels. If the pixel value on mask is 0,
+*                           the pixel will be ignored when maintaining the joint-histogram. This is useful for applications like optical flow occlusion handling.
+*
+* @sa medianBlur, jointBilateralFilter
+*/
+CV_EXPORTS void weightedMedianFilter(InputArray joint, InputArray src, OutputArray dst, int r, double sigma=25.5, WMFWeightType weightType=WMF_EXP, Mat mask=Mat());
+}
+}
+
+#endif
+#endif

modules/ximgproc/perf/perf_weighted_median_filter.cpp

+/*
+ *  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
+ *  (3 - clause BSD License)
+ *
+ *  Redistribution and use in source and binary forms, with or without modification,
+ *  are permitted provided that the following conditions are met :
+ *
+ *  *Redistributions of source code must retain the above copyright notice,
+ *  this list of conditions and the following disclaimer.
+ *
+ *  * Redistributions 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.
+ *
+ *  * Neither the names of the copyright holders nor the names of the contributors
+ *  may 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 copyright holders 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.
+ */
+
+ #include "perf_precomp.hpp"
+
+ namespace cvtest
+ {
+
+ using std::tr1::tuple;
+ using std::tr1::get;
+ using namespace perf;
+ using namespace testing;
+ using namespace cv;
+ using namespace cv::ximgproc;
+
+ typedef tuple<Size, MatType, int, int, int, WMFWeightType> WMFTestParam;
+ typedef TestBaseWithParam<WMFTestParam> WeightedMedianFilterTest;
+
+ PERF_TEST_P(WeightedMedianFilterTest, perf,
+     Combine(
+     Values(szODD, szQVGA),
+     Values(CV_8U, CV_32F),
+     Values(1, 3),
+     Values(1, 3),
+     Values(3, 5),
+     Values(WMF_EXP, WMF_COS))
+ )
+ {
+     RNG rnd(1);
+
+     WMFTestParam params = GetParam();
+
+     double sigma   = rnd.uniform(20.0, 30.0);
+     Size sz         = get<0>(params);
+     int srcDepth       = get<1>(params);
+     int jCn         = get<2>(params);
+     int srcCn       = get<3>(params);
+     int r = get<4>(params);
+     WMFWeightType weightType = get<5>(params);
+
+     Mat joint(sz, CV_MAKE_TYPE(CV_8U, jCn));
+     Mat src(sz, CV_MAKE_TYPE(srcDepth, srcCn));
+     Mat dst(sz, src.type());
+
+     cv::setNumThreads(cv::getNumberOfCPUs());
+     declare.in(joint, src, WARMUP_RNG).out(dst).tbb_threads(cv::getNumberOfCPUs());
+
+     TEST_CYCLE_N(1)
+     {
+         weightedMedianFilter(joint, src, dst, r, sigma, weightType);
+     }
+
+     SANITY_CHECK_NOTHING();
+ }
+ }

modules/ximgproc/test/test_weighted_median_filter.cpp

+/*
+ *  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
+ *  (3 - clause BSD License)
+ *
+ *  Redistribution and use in source and binary forms, with or without modification,
+ *  are permitted provided that the following conditions are met :
+ *
+ *  *Redistributions of source code must retain the above copyright notice,
+ *  this list of conditions and the following disclaimer.
+ *
+ *  * Redistributions 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.
+ *
+ *  * Neither the names of the copyright holders nor the names of the contributors
+ *  may 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 copyright holders 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.
+ */
+
+#include "test_precomp.hpp"
+
+namespace cvtest
+{
+
+using namespace std;
+using namespace std::tr1;
+using namespace testing;
+using namespace perf;
+using namespace cv;
+using namespace cv::ximgproc;
+
+static string getDataDir()
+{
+    return cvtest::TS::ptr()->get_data_path();
+}
+
+typedef tuple<Size, WMFWeightType> WMFParams;
+typedef TestWithParam<WMFParams> WeightedMedianFilterTest;
+
+TEST_P(WeightedMedianFilterTest, SplatSurfaceAccuracy)
+{
+
+    WMFParams params = GetParam();
+    Size size = get<0>(params);
+    WMFWeightType weightType = get<1>(params);
+
+    RNG rnd(0);
+
+    int guideCn = rnd.uniform(1, 2);
+    if(guideCn==2) guideCn++; //1 or 3 channels
+    Mat guide(size, CV_MAKE_TYPE(CV_8U, guideCn));
+    randu(guide, 0, 255);
+
+    Scalar surfaceValue;
+    int srcCn = rnd.uniform(1, 4);
+    rnd.fill(surfaceValue, RNG::UNIFORM, 0, 255);
+    Mat src(size, CV_MAKE_TYPE(CV_8U, srcCn), surfaceValue);
+
+    int r = int(rnd.uniform(3, 11));
+    double sigma  = rnd.uniform(9.0, 100.0);
+
+    Mat res;
+    weightedMedianFilter(guide, src, res, r, sigma, weightType);
+
+    double normL1 = cvtest::norm(src, res, NORM_L1)/src.total()/src.channels();
+    EXPECT_LE(normL1, 1.0/64);
+}
+
+TEST(WeightedMedianFilterTest, ReferenceAccuracy)
+{
+    string dir = getDataDir() + "cv/edgefilter";
+
+    Mat src = imread(dir + "/kodim23.png");
+    Mat ref = imread(dir + "/fgs/kodim23_lambda=1000_sigma=10.png");
+
+    ASSERT_FALSE(src.empty());
+    ASSERT_FALSE(ref.empty());
+
+    cv::setNumThreads(cv::getNumberOfCPUs());
+    Mat res;
+    weightedMedianFilter(src, src, res, 7);
+
+    double totalMaxError = 1.0/32.0*src.total()*src.channels();
+
+    EXPECT_LE(cvtest::norm(res, ref, NORM_L2), totalMaxError);
+}
+
+INSTANTIATE_TEST_CASE_P(TypicalSET, WeightedMedianFilterTest, Combine(Values(szODD, szQVGA),  Values(WMF_EXP, WMF_IV2, WMF_OFF)));
+
+}