Merge pull request #343 from taka-no-me:fix_nlmeans_2646

This commit is contained in:
Andrey Kamaev 2013-01-28 20:35:39 +04:00 committed by OpenCV Buildbot
commit 09d93af975
4 changed files with 17 additions and 7 deletions

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@ -257,7 +257,7 @@ void FastNlMeansDenoisingInvoker<T>::operator() (const BlockedRange& range) cons
}
for (size_t channel_num = 0; channel_num < sizeof(T); channel_num++)
estimation[channel_num] = (estimation[channel_num] + weights_sum/2) / weights_sum;
estimation[channel_num] = ((unsigned)estimation[channel_num] + weights_sum/2) / weights_sum;
dst_.at<T>(i,j) = saturateCastFromArray<T>(estimation);
}

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@ -287,7 +287,7 @@ void FastNlMeansMultiDenoisingInvoker<T>::operator() (const BlockedRange& range)
}
for (size_t channel_num = 0; channel_num < sizeof(T); channel_num++)
estimation[channel_num] = (estimation[channel_num] + weights_sum / 2) / weights_sum;
estimation[channel_num] = ((unsigned)estimation[channel_num] + weights_sum / 2) / weights_sum;
dst_.at<T>(i,j) = saturateCastFromArray<T>(estimation);

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@ -56,7 +56,7 @@ using namespace std;
#endif
TEST(Imgproc_DenoisingGrayscale, regression)
TEST(Photo_DenoisingGrayscale, regression)
{
string folder = string(cvtest::TS::ptr()->get_data_path()) + "denoising/";
string original_path = folder + "lena_noised_gaussian_sigma=10.png";
@ -76,7 +76,7 @@ TEST(Imgproc_DenoisingGrayscale, regression)
ASSERT_EQ(0, norm(result != expected));
}
TEST(Imgproc_DenoisingColored, regression)
TEST(Photo_DenoisingColored, regression)
{
string folder = string(cvtest::TS::ptr()->get_data_path()) + "denoising/";
string original_path = folder + "lena_noised_gaussian_sigma=10.png";
@ -96,7 +96,7 @@ TEST(Imgproc_DenoisingColored, regression)
ASSERT_EQ(0, norm(result != expected));
}
TEST(Imgproc_DenoisingGrayscaleMulti, regression)
TEST(Photo_DenoisingGrayscaleMulti, regression)
{
const int imgs_count = 3;
string folder = string(cvtest::TS::ptr()->get_data_path()) + "denoising/";
@ -121,7 +121,7 @@ TEST(Imgproc_DenoisingGrayscaleMulti, regression)
ASSERT_EQ(0, norm(result != expected));
}
TEST(Imgproc_DenoisingColoredMulti, regression)
TEST(Photo_DenoisingColoredMulti, regression)
{
const int imgs_count = 3;
string folder = string(cvtest::TS::ptr()->get_data_path()) + "denoising/";
@ -146,3 +146,13 @@ TEST(Imgproc_DenoisingColoredMulti, regression)
ASSERT_EQ(0, norm(result != expected));
}
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);
}

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@ -115,4 +115,4 @@ void CV_InpaintTest::run( int )
ts->set_failed_test_info(cvtest::TS::OK);
}
TEST(Imgproc_Inpaint, regression) { CV_InpaintTest test; test.safe_run(); }
TEST(Photo_Inpaint, regression) { CV_InpaintTest test; test.safe_run(); }