test_denoising.cpp 6 KB
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//  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
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
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// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
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#include "test_precomp.hpp"
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#include "opencv2/photo/photo.hpp"
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#include <string>

using namespace cv;
using namespace std;

//#define DUMP_RESULTS

#ifdef DUMP_RESULTS
#  define DUMP(image, path) imwrite(path, image)
#else
#  define DUMP(image, path)
#endif


TEST(Photo_DenoisingGrayscale, regression)
{
    string folder = string(cvtest::TS::ptr()->get_data_path()) + "denoising/";
    string original_path = folder + "lena_noised_gaussian_sigma=10.png";
    string expected_path = folder + "lena_noised_denoised_grayscale_tw=7_sw=21_h=10.png";

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    Mat original = imread(original_path, CV_LOAD_IMAGE_GRAYSCALE);
    Mat expected = imread(expected_path, CV_LOAD_IMAGE_GRAYSCALE);
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    ASSERT_FALSE(original.empty()) << "Could not load input image " << original_path;
    ASSERT_FALSE(expected.empty()) << "Could not load reference image " << expected_path;

    Mat result;
    fastNlMeansDenoising(original, result, 10);

    DUMP(result, expected_path + ".res.png");

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    ASSERT_EQ(0, norm(result != expected));
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}

TEST(Photo_DenoisingColored, regression)
{
    string folder = string(cvtest::TS::ptr()->get_data_path()) + "denoising/";
    string original_path = folder + "lena_noised_gaussian_sigma=10.png";
    string expected_path = folder + "lena_noised_denoised_lab12_tw=7_sw=21_h=10_h2=10.png";

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    Mat original = imread(original_path, CV_LOAD_IMAGE_COLOR);
    Mat expected = imread(expected_path, CV_LOAD_IMAGE_COLOR);
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    ASSERT_FALSE(original.empty()) << "Could not load input image " << original_path;
    ASSERT_FALSE(expected.empty()) << "Could not load reference image " << expected_path;

    Mat result;
    fastNlMeansDenoisingColored(original, result, 10, 10);

    DUMP(result, expected_path + ".res.png");

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    ASSERT_EQ(0, norm(result != expected));
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}

TEST(Photo_DenoisingGrayscaleMulti, regression)
{
    const int imgs_count = 3;
    string folder = string(cvtest::TS::ptr()->get_data_path()) + "denoising/";

    string expected_path = folder + "lena_noised_denoised_multi_tw=7_sw=21_h=15.png";
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    Mat expected = imread(expected_path, CV_LOAD_IMAGE_GRAYSCALE);
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    ASSERT_FALSE(expected.empty()) << "Could not load reference image " << expected_path;

    vector<Mat> original(imgs_count);
    for (int i = 0; i < imgs_count; i++)
    {
        string original_path = format("%slena_noised_gaussian_sigma=20_multi_%d.png", folder.c_str(), i);
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        original[i] = imread(original_path, CV_LOAD_IMAGE_GRAYSCALE);
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        ASSERT_FALSE(original[i].empty()) << "Could not load input image " << original_path;
    }

    Mat result;
    fastNlMeansDenoisingMulti(original, result, imgs_count / 2, imgs_count, 15);

    DUMP(result, expected_path + ".res.png");

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    ASSERT_EQ(0, norm(result != expected));
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}

TEST(Photo_DenoisingColoredMulti, regression)
{
    const int imgs_count = 3;
    string folder = string(cvtest::TS::ptr()->get_data_path()) + "denoising/";

    string expected_path = folder + "lena_noised_denoised_multi_lab12_tw=7_sw=21_h=10_h2=15.png";
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    Mat expected = imread(expected_path, CV_LOAD_IMAGE_COLOR);
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    ASSERT_FALSE(expected.empty()) << "Could not load reference image " << expected_path;

    vector<Mat> original(imgs_count);
    for (int i = 0; i < imgs_count; i++)
    {
        string original_path = format("%slena_noised_gaussian_sigma=20_multi_%d.png", folder.c_str(), i);
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        original[i] = imread(original_path, CV_LOAD_IMAGE_COLOR);
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        ASSERT_FALSE(original[i].empty()) << "Could not load input image " << original_path;
    }

    Mat result;
    fastNlMeansDenoisingColoredMulti(original, result, imgs_count / 2, imgs_count, 10, 15);

    DUMP(result, expected_path + ".res.png");

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    ASSERT_EQ(0, norm(result != expected));
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}

TEST(Photo_White, issue_2646)
{
    cv::Mat img(50, 50, CV_8UC1, cv::Scalar::all(255));
    cv::Mat filtered;
    cv::fastNlMeansDenoising(img, filtered);

    int nonWhitePixelsCount = (int)img.total() - cv::countNonZero(filtered == img);

    ASSERT_EQ(0, nonWhitePixelsCount);
}