2013-09-30 08:27:43 +08:00
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// loss of use, data, or profits; or business interruption) however caused
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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2013-08-19 17:19:52 +08:00
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#include "test_precomp.hpp"
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2014-04-09 04:00:13 +08:00
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void make_noisy(const cv::Mat& img, cv::Mat& noisy, double sigma, double pepper_salt_ratio,cv::RNG& rng)
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{
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2013-08-19 17:19:52 +08:00
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noisy.create(img.size(), img.type());
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cv::Mat noise(img.size(), img.type()), mask(img.size(), CV_8U);
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rng.fill(noise,cv::RNG::NORMAL,128.0,sigma);
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cv::addWeighted(img, 1, noise, 1, -128, noisy);
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cv::randn(noise, cv::Scalar::all(0), cv::Scalar::all(2));
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noise *= 255;
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2013-09-01 13:59:15 +08:00
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cv::randu(mask, 0, cvRound(1./pepper_salt_ratio));
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2013-08-19 17:19:52 +08:00
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cv::Mat half = mask.colRange(0, img.cols/2);
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half = cv::Scalar::all(1);
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noise.setTo(128, mask);
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cv::addWeighted(noisy, 1, noise, 1, -128, noisy);
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}
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2014-04-09 04:00:13 +08:00
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void make_spotty(cv::Mat& img,cv::RNG& rng, int r=3,int n=1000)
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{
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for(int i=0;i<n;i++)
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{
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2013-08-19 17:19:52 +08:00
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int x=rng(img.cols-r),y=rng(img.rows-r);
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2014-04-09 04:00:13 +08:00
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if(rng(2)==0)
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2013-08-19 17:19:52 +08:00
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img(cv::Range(y,y+r),cv::Range(x,x+r))=(uchar)0;
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2014-04-09 04:00:13 +08:00
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else
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2013-08-19 17:19:52 +08:00
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img(cv::Range(y,y+r),cv::Range(x,x+r))=(uchar)255;
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}
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}
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2014-04-09 04:00:13 +08:00
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bool validate_pixel(const cv::Mat& image,int x,int y,uchar val)
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{
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2013-08-19 17:19:52 +08:00
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printf("test: image(%d,%d)=%d vs %d - %s\n",x,y,(int)image.at<uchar>(x,y),val,(val==image.at<uchar>(x,y))?"true":"false");
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2014-08-14 16:50:07 +08:00
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return std::abs(image.at<uchar>(x,y) - val) < 10;
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2013-08-19 17:19:52 +08:00
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}
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2014-04-09 04:00:13 +08:00
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TEST(Optim_denoise_tvl1, regression_basic)
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{
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2013-08-19 17:19:52 +08:00
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cv::RNG rng(42);
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2014-04-09 04:00:13 +08:00
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cv::Mat img = cv::imread(cvtest::TS::ptr()->get_data_path() + "shared/lena.png", 0), noisy, res;
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ASSERT_FALSE(img.empty()) << "Error: can't open 'lena.png'";
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2013-08-19 17:19:52 +08:00
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const int obs_num=5;
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2014-04-09 04:00:13 +08:00
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std::vector<cv::Mat> images(obs_num, cv::Mat());
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for(int i=0;i<(int)images.size();i++)
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{
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2013-08-19 17:19:52 +08:00
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make_noisy(img,images[i], 20, 0.02,rng);
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//make_spotty(images[i],rng);
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}
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//cv::imshow("test", images[0]);
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2014-08-14 16:50:07 +08:00
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cv::denoise_TVL1(images, res);
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2013-08-19 17:19:52 +08:00
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//cv::imshow("denoised", res);
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//cv::waitKey();
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#if 0
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ASSERT_TRUE(validate_pixel(res,248,334,179));
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ASSERT_TRUE(validate_pixel(res,489,333,172));
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ASSERT_TRUE(validate_pixel(res,425,507,104));
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ASSERT_TRUE(validate_pixel(res,489,486,105));
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ASSERT_TRUE(validate_pixel(res,223,208,64));
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ASSERT_TRUE(validate_pixel(res,418,3,78));
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ASSERT_TRUE(validate_pixel(res,63,76,97));
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ASSERT_TRUE(validate_pixel(res,29,134,126));
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ASSERT_TRUE(validate_pixel(res,219,291,174));
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ASSERT_TRUE(validate_pixel(res,384,124,76));
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#endif
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#if 1
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ASSERT_TRUE(validate_pixel(res,248,334,194));
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ASSERT_TRUE(validate_pixel(res,489,333,171));
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ASSERT_TRUE(validate_pixel(res,425,507,103));
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ASSERT_TRUE(validate_pixel(res,489,486,109));
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ASSERT_TRUE(validate_pixel(res,223,208,72));
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ASSERT_TRUE(validate_pixel(res,418,3,58));
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ASSERT_TRUE(validate_pixel(res,63,76,93));
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ASSERT_TRUE(validate_pixel(res,29,134,127));
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ASSERT_TRUE(validate_pixel(res,219,291,180));
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ASSERT_TRUE(validate_pixel(res,384,124,80));
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#endif
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}
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