Open Source Computer Vision Library https://opencv.org/
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/*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) 2013, OpenCV Foundation, 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,
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// * The name of the copyright holders may not be used to endorse or promote products
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// This software is provided by the copyright holders and contributors "as is" and
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// or tort (including negligence or otherwise) arising in any way out of
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//M*/
#include "test_precomp.hpp"
void make_noisy(const cv::Mat& img, cv::Mat& noisy, double sigma, double pepper_salt_ratio,cv::RNG& rng)
{
noisy.create(img.size(), img.type());
cv::Mat noise(img.size(), img.type()), mask(img.size(), CV_8U);
rng.fill(noise,cv::RNG::NORMAL,128.0,sigma);
cv::addWeighted(img, 1, noise, 1, -128, noisy);
cv::randn(noise, cv::Scalar::all(0), cv::Scalar::all(2));
noise *= 255;
cv::randu(mask, 0, cvRound(1./pepper_salt_ratio));
cv::Mat half = mask.colRange(0, img.cols/2);
half = cv::Scalar::all(1);
noise.setTo(128, mask);
cv::addWeighted(noisy, 1, noise, 1, -128, noisy);
}
void make_spotty(cv::Mat& img,cv::RNG& rng, int r=3,int n=1000)
{
for(int i=0;i<n;i++)
{
int x=rng(img.cols-r),y=rng(img.rows-r);
if(rng(2)==0)
img(cv::Range(y,y+r),cv::Range(x,x+r))=(uchar)0;
else
img(cv::Range(y,y+r),cv::Range(x,x+r))=(uchar)255;
}
}
bool validate_pixel(const cv::Mat& image,int x,int y,uchar val)
{
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");
return (image.at<uchar>(x,y)==val);
}
TEST(Optim_denoise_tvl1, regression_basic)
{
cv::RNG rng(42);
cv::Mat img = cv::imread(cvtest::TS::ptr()->get_data_path() + "shared/lena.png", 0), noisy, res;
ASSERT_FALSE(img.empty()) << "Error: can't open 'lena.png'";
const int obs_num=5;
std::vector<cv::Mat> images(obs_num, cv::Mat());
for(int i=0;i<(int)images.size();i++)
{
make_noisy(img,images[i], 20, 0.02,rng);
//make_spotty(images[i],rng);
}
//cv::imshow("test", images[0]);
cv::optim::denoise_TVL1(images, res);
//cv::imshow("denoised", res);
//cv::waitKey();
#if 0
ASSERT_TRUE(validate_pixel(res,248,334,179));
ASSERT_TRUE(validate_pixel(res,489,333,172));
ASSERT_TRUE(validate_pixel(res,425,507,104));
ASSERT_TRUE(validate_pixel(res,489,486,105));
ASSERT_TRUE(validate_pixel(res,223,208,64));
ASSERT_TRUE(validate_pixel(res,418,3,78));
ASSERT_TRUE(validate_pixel(res,63,76,97));
ASSERT_TRUE(validate_pixel(res,29,134,126));
ASSERT_TRUE(validate_pixel(res,219,291,174));
ASSERT_TRUE(validate_pixel(res,384,124,76));
#endif
#if 1
ASSERT_TRUE(validate_pixel(res,248,334,194));
ASSERT_TRUE(validate_pixel(res,489,333,171));
ASSERT_TRUE(validate_pixel(res,425,507,103));
ASSERT_TRUE(validate_pixel(res,489,486,109));
ASSERT_TRUE(validate_pixel(res,223,208,72));
ASSERT_TRUE(validate_pixel(res,418,3,58));
ASSERT_TRUE(validate_pixel(res,63,76,93));
ASSERT_TRUE(validate_pixel(res,29,134,127));
ASSERT_TRUE(validate_pixel(res,219,291,180));
ASSERT_TRUE(validate_pixel(res,384,124,80));
#endif
}