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opencv/modules/photo/src/denoising.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
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// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// are permitted provided that the following conditions are met:
//
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// this list of conditions and the following disclaimer.
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#include "precomp.hpp"
#include "fast_nlmeans_denoising_invoker.hpp"
#include "fast_nlmeans_multi_denoising_invoker.hpp"
#include "fast_nlmeans_denoising_opencl.hpp"
void cv::fastNlMeansDenoising( InputArray _src, OutputArray _dst, float h,
int templateWindowSize, int searchWindowSize)
{
Size src_size = _src.size();
CV_OCL_RUN(_src.dims() <= 2 && (_src.isUMat() || _dst.isUMat()) &&
src_size.width > 5 && src_size.height > 5, // low accuracy on small sizes
ocl_fastNlMeansDenoising(_src, _dst, &h, 1,
templateWindowSize, searchWindowSize, false))
Mat src = _src.getMat();
_dst.create(src_size, src.type());
Mat dst = _dst.getMat();
#ifdef HAVE_TEGRA_OPTIMIZATION
if(tegra::fastNlMeansDenoising(src, dst, h, templateWindowSize, searchWindowSize))
return;
#endif
switch (src.type()) {
case CV_8U:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<uchar, int, unsigned, DistSquared, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC2:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec2b, int, unsigned, DistSquared, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC3:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec3b, int, unsigned, DistSquared, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC4:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec4b, int, unsigned, DistSquared, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
default:
CV_Error(Error::StsBadArg,
"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3 and CV_8UC4 are supported");
}
}
void cv::fastNlMeansDenoising( InputArray _src, OutputArray _dst, float *h,
int templateWindowSize, int searchWindowSize)
{
Size src_size = _src.size();
CV_OCL_RUN(_src.dims() <= 2 && (_src.isUMat() || _dst.isUMat()) &&
src_size.width > 5 && src_size.height > 5, // low accuracy on small sizes
ocl_fastNlMeansDenoising(_src, _dst, h, CV_MAT_CN(_src.type()),
templateWindowSize, searchWindowSize, false))
Mat src = _src.getMat();
_dst.create(src_size, src.type());
Mat dst = _dst.getMat();
#ifdef HAVE_TEGRA_OPTIMIZATION
if(tegra::fastNlMeansDenoising(src, dst, h, templateWindowSize, searchWindowSize))
return;
#endif
switch (src.type()) {
case CV_8U:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<uchar, int, unsigned, DistSquared, int>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC2:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec2b, int, unsigned, DistSquared, Vec2i>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC3:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec3b, int, unsigned, DistSquared, Vec3i>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC4:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec4b, int, unsigned, DistSquared, Vec4i>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
default:
CV_Error(Error::StsBadArg,
"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3 and CV_8UC4 are supported");
}
}
void cv::fastNlMeansDenoisingAbs( InputArray _src, OutputArray _dst, float h,
int templateWindowSize, int searchWindowSize)
{
Size src_size = _src.size();
CV_OCL_RUN(_src.dims() <= 2 && (_src.isUMat() || _dst.isUMat()) &&
src_size.width > 5 && src_size.height > 5, // low accuracy on small sizes
ocl_fastNlMeansDenoising(_src, _dst, &h, 1,
templateWindowSize, searchWindowSize, true))
Mat src = _src.getMat();
_dst.create(src_size, src.type());
Mat dst = _dst.getMat();
switch (src.type()) {
case CV_8U:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<uchar, int, unsigned, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC2:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec2b, int, unsigned, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC3:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec3b, int, unsigned, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC4:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec4b, int, unsigned, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_16U:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<ushort, int64, uint64, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_16UC2:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec<ushort, 2>, int64, uint64, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_16UC3:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec<ushort, 3>, int64, uint64, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_16UC4:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec<ushort, 4>, int64, uint64, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, &h));
break;
default:
CV_Error(Error::StsBadArg,
"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3, CV_8UC4, CV_16U, CV_16UC2, CV_16UC3 and CV_16UC4 are supported");
}
}
void cv::fastNlMeansDenoisingAbs( InputArray _src, OutputArray _dst, float *h,
int templateWindowSize, int searchWindowSize)
{
Size src_size = _src.size();
CV_OCL_RUN(_src.dims() <= 2 && (_src.isUMat() || _dst.isUMat()) &&
src_size.width > 5 && src_size.height > 5, // low accuracy on small sizes
ocl_fastNlMeansDenoising(_src, _dst, h, CV_MAT_CN(_src.type()),
templateWindowSize, searchWindowSize, true))
Mat src = _src.getMat();
_dst.create(src_size, src.type());
Mat dst = _dst.getMat();
switch (src.type()) {
case CV_8U:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<uchar, int, unsigned, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC2:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec2b, int, unsigned, DistAbs, Vec2i>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC3:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec3b, int, unsigned, DistAbs, Vec3i>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC4:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec4b, int, unsigned, DistAbs, Vec4i>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_16U:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<ushort, int64, uint64, DistAbs, int>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_16UC2:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec<ushort, 2>, int64, uint64, DistAbs, Vec2i>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_16UC3:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec<ushort, 3>, int64, uint64, DistAbs, Vec3i>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
case CV_16UC4:
parallel_for_(cv::Range(0, src.rows),
FastNlMeansDenoisingInvoker<cv::Vec<ushort, 4>, int64, uint64, DistAbs, Vec4i>(
src, dst, templateWindowSize, searchWindowSize, h));
break;
default:
CV_Error(Error::StsBadArg,
"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3, CV_8UC4, CV_16U, CV_16UC2, CV_16UC3 and CV_16UC4 are supported");
}
}
void cv::fastNlMeansDenoisingColored( InputArray _src, OutputArray _dst,
float h, float hForColorComponents,
int templateWindowSize, int searchWindowSize)
{
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
Size src_size = _src.size();
if (type != CV_8UC3 && type != CV_8UC4)
{
CV_Error(Error::StsBadArg, "Type of input image should be CV_8UC3 or CV_8UC4!");
return;
}
CV_OCL_RUN(_src.dims() <= 2 && (_dst.isUMat() || _src.isUMat()) &&
src_size.width > 5 && src_size.height > 5, // low accuracy on small sizes
ocl_fastNlMeansDenoisingColored(_src, _dst, h, hForColorComponents,
templateWindowSize, searchWindowSize))
Mat src = _src.getMat();
_dst.create(src_size, type);
Mat dst = _dst.getMat();
Mat src_lab;
cvtColor(src, src_lab, COLOR_LBGR2Lab);
Mat l(src_size, CV_MAKE_TYPE(depth, 1));
Mat ab(src_size, CV_MAKE_TYPE(depth, 2));
Mat l_ab[] = { l, ab };
int from_to[] = { 0,0, 1,1, 2,2 };
mixChannels(&src_lab, 1, l_ab, 2, from_to, 3);
fastNlMeansDenoising(l, l, h, templateWindowSize, searchWindowSize);
fastNlMeansDenoising(ab, ab, hForColorComponents, templateWindowSize, searchWindowSize);
Mat l_ab_denoised[] = { l, ab };
Mat dst_lab(src_size, CV_MAKE_TYPE(depth, 3));
mixChannels(l_ab_denoised, 2, &dst_lab, 1, from_to, 3);
cvtColor(dst_lab, dst, COLOR_Lab2LBGR, cn);
}
static void fastNlMeansDenoisingMultiCheckPreconditions(
const std::vector<Mat>& srcImgs,
int imgToDenoiseIndex, int temporalWindowSize,
int templateWindowSize, int searchWindowSize)
{
int src_imgs_size = static_cast<int>(srcImgs.size());
if (src_imgs_size == 0)
{
CV_Error(Error::StsBadArg, "Input images vector should not be empty!");
}
if (temporalWindowSize % 2 == 0 ||
searchWindowSize % 2 == 0 ||
templateWindowSize % 2 == 0) {
CV_Error(Error::StsBadArg, "All windows sizes should be odd!");
}
int temporalWindowHalfSize = temporalWindowSize / 2;
if (imgToDenoiseIndex - temporalWindowHalfSize < 0 ||
imgToDenoiseIndex + temporalWindowHalfSize >= src_imgs_size)
{
CV_Error(Error::StsBadArg,
"imgToDenoiseIndex and temporalWindowSize "
"should be chosen corresponding srcImgs size!");
}
for (int i = 1; i < src_imgs_size; i++)
if (srcImgs[0].size() != srcImgs[i].size() || srcImgs[0].type() != srcImgs[i].type())
{
CV_Error(Error::StsBadArg, "Input images should have the same size and type!");
}
}
void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _dst,
int imgToDenoiseIndex, int temporalWindowSize,
float h, int templateWindowSize, int searchWindowSize)
{
std::vector<Mat> srcImgs;
_srcImgs.getMatVector(srcImgs);
fastNlMeansDenoisingMultiCheckPreconditions(
srcImgs, imgToDenoiseIndex,
temporalWindowSize, templateWindowSize, searchWindowSize);
_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<uchar, int, unsigned, DistSquared, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC2:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec2b, int, unsigned, DistSquared, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC3:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec3b, int, unsigned, DistSquared, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC4:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec4b, int, unsigned, DistSquared, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
default:
CV_Error(Error::StsBadArg,
"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3 and CV_8UC4 are supported");
}
}
void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _dst,
int imgToDenoiseIndex, int temporalWindowSize,
float *h, int templateWindowSize, int searchWindowSize)
{
std::vector<Mat> srcImgs;
_srcImgs.getMatVector(srcImgs);
fastNlMeansDenoisingMultiCheckPreconditions(
srcImgs, imgToDenoiseIndex,
temporalWindowSize, templateWindowSize, searchWindowSize);
_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<uchar, int, unsigned, DistSquared, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC2:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec2b, int, unsigned, DistSquared, Vec2i>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC3:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec3b, int, unsigned, DistSquared, Vec3i>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC4:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec4b, int, unsigned, DistSquared, Vec4i>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
default:
CV_Error(Error::StsBadArg,
"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3 and CV_8UC4 are supported");
}
}
void cv::fastNlMeansDenoisingMultiAbs( InputArrayOfArrays _srcImgs, OutputArray _dst,
int imgToDenoiseIndex, int temporalWindowSize,
float h, int templateWindowSize, int searchWindowSize)
{
std::vector<Mat> srcImgs;
_srcImgs.getMatVector(srcImgs);
fastNlMeansDenoisingMultiCheckPreconditions(
srcImgs, imgToDenoiseIndex,
temporalWindowSize, templateWindowSize, searchWindowSize);
_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<uchar, int, unsigned, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC2:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec2b, int, unsigned, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC3:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec3b, int, unsigned, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_8UC4:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec4b, int, unsigned, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_16U:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<ushort, int64, uint64, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_16UC2:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec<ushort, 2>, int64, uint64, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_16UC3:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec<ushort, 3>, int64, uint64, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
case CV_16UC4:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec<ushort, 4>, int64, uint64, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, &h));
break;
default:
CV_Error(Error::StsBadArg,
"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3, CV_8UC4, CV_16U, CV_16UC2, CV_16UC3 and CV_16UC4 are supported");
}
}
void cv::fastNlMeansDenoisingMultiAbs( InputArrayOfArrays _srcImgs, OutputArray _dst,
int imgToDenoiseIndex, int temporalWindowSize,
float *h, int templateWindowSize, int searchWindowSize)
{
std::vector<Mat> srcImgs;
_srcImgs.getMatVector(srcImgs);
fastNlMeansDenoisingMultiCheckPreconditions(
srcImgs, imgToDenoiseIndex,
temporalWindowSize, templateWindowSize, searchWindowSize);
_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<uchar, int, unsigned, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC2:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec2b, int, unsigned, DistAbs, Vec2i>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC3:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec3b, int, unsigned, DistAbs, Vec3i>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_8UC4:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec4b, int, unsigned, DistAbs, Vec4i>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_16U:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<ushort, int64, uint64, DistAbs, int>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_16UC2:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec<ushort, 2>, int64, uint64, DistAbs, Vec2i>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_16UC3:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec<ushort, 3>, int64, uint64, DistAbs, Vec3i>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
case CV_16UC4:
parallel_for_(cv::Range(0, srcImgs[0].rows),
FastNlMeansMultiDenoisingInvoker<cv::Vec<ushort, 4>, int64, uint64, DistAbs, Vec4i>(
srcImgs, imgToDenoiseIndex, temporalWindowSize,
dst, templateWindowSize, searchWindowSize, h));
break;
default:
CV_Error(Error::StsBadArg,
"Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3, CV_8UC4, CV_16U, CV_16UC2, CV_16UC3 and CV_16UC4 are supported");
}
}
void cv::fastNlMeansDenoisingColoredMulti( InputArrayOfArrays _srcImgs, OutputArray _dst,
int imgToDenoiseIndex, int temporalWindowSize,
float h, float hForColorComponents,
int templateWindowSize, int searchWindowSize)
{
std::vector<Mat> srcImgs;
_srcImgs.getMatVector(srcImgs);
fastNlMeansDenoisingMultiCheckPreconditions(
srcImgs, imgToDenoiseIndex,
temporalWindowSize, templateWindowSize, searchWindowSize);
_dst.create(srcImgs[0].size(), srcImgs[0].type());
Mat dst = _dst.getMat();
int type = srcImgs[0].type(), depth = CV_MAT_DEPTH(type);
int src_imgs_size = static_cast<int>(srcImgs.size());
if (type != CV_8UC3)
{
CV_Error(Error::StsBadArg, "Type of input images should be CV_8UC3!");
return;
}
int from_to[] = { 0,0, 1,1, 2,2 };
// TODO convert only required images
std::vector<Mat> src_lab(src_imgs_size);
std::vector<Mat> l(src_imgs_size);
std::vector<Mat> ab(src_imgs_size);
for (int i = 0; i < src_imgs_size; i++)
{
src_lab[i] = Mat::zeros(srcImgs[0].size(), type);
l[i] = Mat::zeros(srcImgs[0].size(), CV_MAKE_TYPE(depth, 1));
ab[i] = Mat::zeros(srcImgs[0].size(), CV_MAKE_TYPE(depth, 2));
cvtColor(srcImgs[i], src_lab[i], COLOR_LBGR2Lab);
Mat l_ab[] = { l[i], ab[i] };
mixChannels(&src_lab[i], 1, l_ab, 2, from_to, 3);
}
Mat dst_l;
Mat dst_ab;
fastNlMeansDenoisingMulti(
l, dst_l, imgToDenoiseIndex, temporalWindowSize,
h, templateWindowSize, searchWindowSize);
fastNlMeansDenoisingMulti(
ab, dst_ab, imgToDenoiseIndex, temporalWindowSize,
hForColorComponents, templateWindowSize, searchWindowSize);
Mat l_ab_denoised[] = { dst_l, dst_ab };
Mat dst_lab(srcImgs[0].size(), srcImgs[0].type());
mixChannels(l_ab_denoised, 2, &dst_lab, 1, from_to, 3);
cvtColor(dst_lab, dst, COLOR_Lab2LBGR);
}
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