cameracv/libs/opencv/modules/photo/test/test_denoise_tvl1.cpp

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#include "test_precomp.hpp"

namespace opencv_test { namespace {

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);
}

#if 0
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;
    }
}
#endif

bool validate_pixel(const cv::Mat& image,int x,int y,uchar val)
{
    bool ok = std::abs(image.at<uchar>(x,y) - val) < 10;
    printf("test: image(%d,%d)=%d vs %d - %s\n",x,y,(int)image.at<uchar>(x,y),val,ok?"ok":"bad");
    return ok;
}

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::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

}

}} // namespace