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ccc71ac190
This is an implementation of primal-dual algorithm, based on the C++ source code by Vadim Pisarevsky. It was extended to handle the denoising based on multiple observations. It also contains documentation and tests.
82 lines
2.9 KiB
C++
82 lines
2.9 KiB
C++
#include "test_precomp.hpp"
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#include "opencv2/highgui.hpp"
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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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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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cv::randu(mask, 0, round(1./pepper_salt_ratio));
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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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void make_spotty(cv::Mat& img,cv::RNG& rng, int r=3,int n=1000){
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for(int i=0;i<n;i++){
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int x=rng(img.cols-r),y=rng(img.rows-r);
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if(rng(2)==0){
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img(cv::Range(y,y+r),cv::Range(x,x+r))=(uchar)0;
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}else{
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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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}
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bool validate_pixel(const cv::Mat& image,int x,int y,uchar val){
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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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return (image.at<uchar>(x,y)==val);
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}
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TEST(Optim_denoise_tvl1, regression_basic){
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cv::RNG rng(42);
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cv::Mat img = cv::imread("lena.jpg", 0), noisy,res;
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if(img.rows!=512 || img.cols!=512){
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printf("\tplease, put lena.jpg from samples/c in the current folder\n");
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printf("\tnow, the test will fail...\n");
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ASSERT_TRUE(false);
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}
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const int obs_num=5;
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std::vector<cv::Mat> images(obs_num,cv::Mat());
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for(int i=0;i<images.size();i++){
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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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cv::optim::denoise_TVL1(images, res);
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printf("hello here!\n");
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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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