diff --git a/modules/photo/include/opencv2/photo.hpp b/modules/photo/include/opencv2/photo.hpp index 0a42424cb4..c651b9ee33 100644 --- a/modules/photo/include/opencv2/photo.hpp +++ b/modules/photo/include/opencv2/photo.hpp @@ -142,7 +142,8 @@ CV_EXPORTS_W void fastNlMeansDenoising( InputArray src, OutputArray dst, float h with several computational optimizations. Noise expected to be a gaussian white noise -@param src Input 8-bit 1-channel, 2-channel, 3-channel or 4-channel image. +@param src Input 8-bit or 16-bit (only with NORM_L1) 1-channel, +2-channel, 3-channel or 4-channel image. @param dst Output image with the same size and type as src . @param templateWindowSize Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels @@ -153,7 +154,7 @@ denoising time. Recommended value 21 pixels parameter applied to all channels or one per channel in dst. Big h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise -@param normType Type of norm used for weight calcluation. Can be either NORM_L2 or NORM_L1 +@param normType Type of norm used for weight calculation. Can be either NORM_L2 or NORM_L1 This function expected to be applied to grayscale images. For colored images look at fastNlMeansDenoisingColored. Advanced usage of this functions can be manual denoising of colored @@ -220,9 +221,9 @@ captured in small period of time. For example video. This version of the functio images or for manual manipulation with colorspaces. For more details see -@param srcImgs Input 8-bit 1-channel, 2-channel, 3-channel or -4-channel images sequence. All images should have the same type and -size. +@param srcImgs Input 8-bit or 16-bit (only with NORM_L1) 1-channel, +2-channel, 3-channel or 4-channel images sequence. All images should +have the same type and size. @param imgToDenoiseIndex Target image to denoise index in srcImgs sequence @param temporalWindowSize Number of surrounding images to use for target image denoising. Should be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to @@ -238,10 +239,13 @@ denoising time. Recommended value 21 pixels parameter applied to all channels or one per channel in dst. Big h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise +@param normType Type of norm used for weight calculation. Can be either NORM_L2 or NORM_L1 */ CV_EXPORTS_W void fastNlMeansDenoisingMulti( InputArrayOfArrays srcImgs, OutputArray dst, - int imgToDenoiseIndex, int temporalWindowSize, - const std::vector& h , int templateWindowSize = 7, int searchWindowSize = 21); + int imgToDenoiseIndex, int temporalWindowSize, + const std::vector& h, + int templateWindowSize = 7, int searchWindowSize = 21, + int normType = NORM_L2); /** @brief Modification of fastNlMeansDenoisingMulti function for colored images sequences diff --git a/modules/photo/src/denoising.cpp b/modules/photo/src/denoising.cpp index 4e7922e40c..c68d09b925 100644 --- a/modules/photo/src/denoising.cpp +++ b/modules/photo/src/denoising.cpp @@ -230,73 +230,55 @@ static void fastNlMeansDenoisingMultiCheckPreconditions( } } -void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _dst, - int imgToDenoiseIndex, int temporalWindowSize, - float h, int templateWindowSize, int searchWindowSize) -{ - fastNlMeansDenoisingMulti(_srcImgs, _dst, imgToDenoiseIndex, temporalWindowSize, - std::vector(1, h), templateWindowSize, searchWindowSize); -} - -void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _dst, - int imgToDenoiseIndex, int temporalWindowSize, - const std::vector& h, - int templateWindowSize, int searchWindowSize) +template +static void fastNlMeansDenoisingMulti_( const std::vector& srcImgs, Mat& dst, + int imgToDenoiseIndex, int temporalWindowSize, + const std::vector& h, + int templateWindowSize, int searchWindowSize) { - std::vector srcImgs; - _srcImgs.getMatVector(srcImgs); - - fastNlMeansDenoisingMultiCheckPreconditions( - srcImgs, imgToDenoiseIndex, - temporalWindowSize, templateWindowSize, searchWindowSize); - int hn = (int)h.size(); - CV_Assert(hn == 1 || hn == CV_MAT_CN(srcImgs[0].type())); - - _dst.create(srcImgs[0].size(), srcImgs[0].type()); - Mat dst = _dst.getMat(); switch (srcImgs[0].type()) { case CV_8U: parallel_for_(cv::Range(0, srcImgs[0].rows), - FastNlMeansMultiDenoisingInvoker( + FastNlMeansMultiDenoisingInvoker( srcImgs, imgToDenoiseIndex, temporalWindowSize, dst, templateWindowSize, searchWindowSize, &h[0])); break; case CV_8UC2: if (hn == 1) parallel_for_(cv::Range(0, srcImgs[0].rows), - FastNlMeansMultiDenoisingInvoker( + FastNlMeansMultiDenoisingInvoker, IT, UIT, D, int>( srcImgs, imgToDenoiseIndex, temporalWindowSize, dst, templateWindowSize, searchWindowSize, &h[0])); else parallel_for_(cv::Range(0, srcImgs[0].rows), - FastNlMeansMultiDenoisingInvoker( + FastNlMeansMultiDenoisingInvoker, IT, UIT, D, Vec2i>( srcImgs, imgToDenoiseIndex, temporalWindowSize, dst, templateWindowSize, searchWindowSize, &h[0])); break; case CV_8UC3: if (hn == 1) parallel_for_(cv::Range(0, srcImgs[0].rows), - FastNlMeansMultiDenoisingInvoker( + FastNlMeansMultiDenoisingInvoker, IT, UIT, D, int>( srcImgs, imgToDenoiseIndex, temporalWindowSize, dst, templateWindowSize, searchWindowSize, &h[0])); else parallel_for_(cv::Range(0, srcImgs[0].rows), - FastNlMeansMultiDenoisingInvoker( + FastNlMeansMultiDenoisingInvoker, IT, UIT, D, Vec3i>( srcImgs, imgToDenoiseIndex, temporalWindowSize, dst, templateWindowSize, searchWindowSize, &h[0])); break; case CV_8UC4: if (hn == 1) parallel_for_(cv::Range(0, srcImgs[0].rows), - FastNlMeansMultiDenoisingInvoker( + FastNlMeansMultiDenoisingInvoker, IT, UIT, D, int>( srcImgs, imgToDenoiseIndex, temporalWindowSize, dst, templateWindowSize, searchWindowSize, &h[0])); else parallel_for_(cv::Range(0, srcImgs[0].rows), - FastNlMeansMultiDenoisingInvoker( + FastNlMeansMultiDenoisingInvoker, IT, UIT, D, Vec4i>( srcImgs, imgToDenoiseIndex, temporalWindowSize, dst, templateWindowSize, searchWindowSize, &h[0])); break; @@ -306,6 +288,75 @@ void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _ds } } +void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _dst, + int imgToDenoiseIndex, int temporalWindowSize, + float h, int templateWindowSize, int searchWindowSize) +{ + fastNlMeansDenoisingMulti(_srcImgs, _dst, imgToDenoiseIndex, temporalWindowSize, + std::vector(1, h), templateWindowSize, searchWindowSize); +} + +void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _dst, + int imgToDenoiseIndex, int temporalWindowSize, + const std::vector& h, + int templateWindowSize, int searchWindowSize, int normType) +{ + std::vector srcImgs; + _srcImgs.getMatVector(srcImgs); + + fastNlMeansDenoisingMultiCheckPreconditions( + srcImgs, imgToDenoiseIndex, + temporalWindowSize, templateWindowSize, searchWindowSize); + + int hn = (int)h.size(); + int type = srcImgs[0].type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type); + CV_Assert(hn == 1 || hn == cn); + + _dst.create(srcImgs[0].size(), srcImgs[0].type()); + Mat dst = _dst.getMat(); + + switch (normType) { + case NORM_L2: + switch (depth) { + case CV_8U: + fastNlMeansDenoisingMulti_(srcImgs, dst, + imgToDenoiseIndex, temporalWindowSize, + h, + templateWindowSize, searchWindowSize); + break; + default: + CV_Error(Error::StsBadArg, + "Unsupported depth! Only CV_8U is supported for NORM_L2"); + } + break; + case NORM_L1: + switch (depth) { + case CV_8U: + fastNlMeansDenoisingMulti_(srcImgs, dst, + imgToDenoiseIndex, temporalWindowSize, + h, + templateWindowSize, searchWindowSize); + break; + case CV_16U: + fastNlMeansDenoisingMulti_(srcImgs, dst, + imgToDenoiseIndex, temporalWindowSize, + h, + templateWindowSize, searchWindowSize); + break; + default: + CV_Error(Error::StsBadArg, + "Unsupported depth! Only CV_8U and CV_16U are supported for NORM_L1"); + } + break; + default: + CV_Error(Error::StsBadArg, + "Unsupported norm type! Only NORM_L2 and NORM_L1 are supported"); + } +} + void cv::fastNlMeansDenoisingColoredMulti( InputArrayOfArrays _srcImgs, OutputArray _dst, int imgToDenoiseIndex, int temporalWindowSize, float h, float hForColorComponents,