Added normType parameter to fastNlMeansDenoisingMulti
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Erik Karlsson
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70a64ebe72
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01d3df0d00
@ -142,7 +142,8 @@ CV_EXPORTS_W void fastNlMeansDenoising( InputArray src, OutputArray dst, float h
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<http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational
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optimizations. Noise expected to be a gaussian white noise
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@param src Input 8-bit 1-channel, 2-channel, 3-channel or 4-channel image.
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@param src Input 8-bit or 16-bit (only with NORM_L1) 1-channel,
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2-channel, 3-channel or 4-channel image.
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@param dst Output image with the same size and type as src .
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@param templateWindowSize Size in pixels of the template patch that is used to compute weights.
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Should be odd. Recommended value 7 pixels
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@ -153,7 +154,7 @@ denoising time. Recommended value 21 pixels
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parameter applied to all channels or one per channel in dst. Big h value
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perfectly removes noise but also removes image details, smaller h
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value preserves details but also preserves some noise
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@param normType Type of norm used for weight calcluation. Can be either NORM_L2 or NORM_L1
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@param normType Type of norm used for weight calculation. Can be either NORM_L2 or NORM_L1
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This function expected to be applied to grayscale images. For colored images look at
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fastNlMeansDenoisingColored. Advanced usage of this functions can be manual denoising of colored
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@ -220,9 +221,9 @@ captured in small period of time. For example video. This version of the functio
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images or for manual manipulation with colorspaces. For more details see
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<http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394>
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@param srcImgs Input 8-bit 1-channel, 2-channel, 3-channel or
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4-channel images sequence. All images should have the same type and
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size.
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@param srcImgs Input 8-bit or 16-bit (only with NORM_L1) 1-channel,
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2-channel, 3-channel or 4-channel images sequence. All images should
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have the same type and size.
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@param imgToDenoiseIndex Target image to denoise index in srcImgs sequence
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@param temporalWindowSize Number of surrounding images to use for target image denoising. Should
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be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to
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@ -238,10 +239,13 @@ denoising time. Recommended value 21 pixels
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parameter applied to all channels or one per channel in dst. Big h value
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perfectly removes noise but also removes image details, smaller h
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value preserves details but also preserves some noise
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@param normType Type of norm used for weight calculation. Can be either NORM_L2 or NORM_L1
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*/
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CV_EXPORTS_W void fastNlMeansDenoisingMulti( InputArrayOfArrays srcImgs, OutputArray dst,
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int imgToDenoiseIndex, int temporalWindowSize,
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const std::vector<float>& h , int templateWindowSize = 7, int searchWindowSize = 21);
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const std::vector<float>& h,
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int templateWindowSize = 7, int searchWindowSize = 21,
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int normType = NORM_L2);
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/** @brief Modification of fastNlMeansDenoisingMulti function for colored images sequences
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@ -230,6 +230,64 @@ static void fastNlMeansDenoisingMultiCheckPreconditions(
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}
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}
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template<typename ST, typename IT, typename UIT, typename D>
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static void fastNlMeansDenoisingMulti_( const std::vector<Mat>& srcImgs, Mat& dst,
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int imgToDenoiseIndex, int temporalWindowSize,
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const std::vector<float>& h,
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int templateWindowSize, int searchWindowSize)
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{
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int hn = (int)h.size();
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switch (srcImgs[0].type())
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{
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case CV_8U:
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<uchar, IT, UIT, D, int>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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break;
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case CV_8UC2:
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if (hn == 1)
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec<ST, 2>, IT, UIT, D, int>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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else
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec<ST, 2>, IT, UIT, D, Vec2i>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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break;
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case CV_8UC3:
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if (hn == 1)
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec<ST, 3>, IT, UIT, D, int>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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else
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec<ST, 3>, IT, UIT, D, Vec3i>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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break;
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case CV_8UC4:
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if (hn == 1)
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec<ST, 4>, IT, UIT, D, int>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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else
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec<ST, 4>, IT, UIT, D, Vec4i>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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break;
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default:
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CV_Error(Error::StsBadArg,
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"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3 and CV_8UC4 are supported");
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}
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}
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void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _dst,
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int imgToDenoiseIndex, int temporalWindowSize,
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float h, int templateWindowSize, int searchWindowSize)
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@ -241,7 +299,7 @@ void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _ds
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void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _dst,
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int imgToDenoiseIndex, int temporalWindowSize,
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const std::vector<float>& h,
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int templateWindowSize, int searchWindowSize)
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int templateWindowSize, int searchWindowSize, int normType)
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{
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std::vector<Mat> srcImgs;
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_srcImgs.getMatVector(srcImgs);
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@ -251,58 +309,51 @@ void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _ds
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temporalWindowSize, templateWindowSize, searchWindowSize);
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int hn = (int)h.size();
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CV_Assert(hn == 1 || hn == CV_MAT_CN(srcImgs[0].type()));
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int type = srcImgs[0].type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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CV_Assert(hn == 1 || hn == cn);
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_dst.create(srcImgs[0].size(), srcImgs[0].type());
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Mat dst = _dst.getMat();
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switch (srcImgs[0].type())
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{
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switch (normType) {
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case NORM_L2:
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switch (depth) {
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case CV_8U:
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<uchar, int, unsigned, DistSquared, int>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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break;
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case CV_8UC2:
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if (hn == 1)
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec2b, int, unsigned, DistSquared, int>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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else
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec2b, int, unsigned, DistSquared, Vec2i>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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break;
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case CV_8UC3:
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if (hn == 1)
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec3b, int, unsigned, DistSquared, int>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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else
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec3b, int, unsigned, DistSquared, Vec3i>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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break;
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case CV_8UC4:
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if (hn == 1)
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec4b, int, unsigned, DistSquared, int>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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else
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parallel_for_(cv::Range(0, srcImgs[0].rows),
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FastNlMeansMultiDenoisingInvoker<Vec4b, int, unsigned, DistSquared, Vec4i>(
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srcImgs, imgToDenoiseIndex, temporalWindowSize,
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dst, templateWindowSize, searchWindowSize, &h[0]));
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fastNlMeansDenoisingMulti_<uchar, int, unsigned,
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DistSquared>(srcImgs, dst,
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imgToDenoiseIndex, temporalWindowSize,
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h,
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templateWindowSize, searchWindowSize);
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break;
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default:
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CV_Error(Error::StsBadArg,
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"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3 and CV_8UC4 are supported");
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"Unsupported depth! Only CV_8U is supported for NORM_L2");
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}
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break;
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case NORM_L1:
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switch (depth) {
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case CV_8U:
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fastNlMeansDenoisingMulti_<uchar, int, unsigned,
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DistAbs>(srcImgs, dst,
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imgToDenoiseIndex, temporalWindowSize,
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h,
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templateWindowSize, searchWindowSize);
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break;
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case CV_16U:
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fastNlMeansDenoisingMulti_<ushort, int64, uint64,
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DistAbs>(srcImgs, dst,
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imgToDenoiseIndex, temporalWindowSize,
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h,
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templateWindowSize, searchWindowSize);
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break;
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default:
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CV_Error(Error::StsBadArg,
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"Unsupported depth! Only CV_8U and CV_16U are supported for NORM_L1");
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}
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break;
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default:
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CV_Error(Error::StsBadArg,
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"Unsupported norm type! Only NORM_L2 and NORM_L1 are supported");
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}
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}
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