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Addition of per-channel h-values for fastNlMeansDenoising[Multi][Abs]

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This commit is contained in:
Erik Karlsson
2015-03-06 20:43:55 +01:00
parent 324fa26848
commit cc8d94c6fc
6 changed files with 344 additions and 11 deletions
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modules/photo/src/denoising.cpp
+221
View File
@@ -90,6 +90,51 @@ void cv::fastNlMeansDenoising( InputArray _src, OutputArray _dst, float h,
}
}
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)
{
@@ -150,6 +195,66 @@ void cv::fastNlMeansDenoisingAbs( InputArray _src, OutputArray _dst, float h,
}
}
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)
@@ -269,6 +374,52 @@ void cv::fastNlMeansDenoisingMulti( InputArrayOfArrays _srcImgs, OutputArray _ds
}
}
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)
@@ -339,6 +490,76 @@ void cv::fastNlMeansDenoisingMultiAbs( InputArrayOfArrays _srcImgs, OutputArray
}
}
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,
modules/photo/src/fast_nlmeans_denoising_invoker.hpp
+1 -1
View File
@@ -236,7 +236,7 @@ void FastNlMeansDenoisingInvoker<T, IT, UIT, D, WT>::operator() (const Range& ra
for (int x = 0; x < search_window_size_; x++)
{
int almostAvgDist = dist_sums_row[x] >> almost_template_window_size_sq_bin_shift_;
int weight = almost_dist2weight_[almostAvgDist];
WT weight = almost_dist2weight_[almostAvgDist];
T p = cur_row_ptr[border_size_ + search_window_x + x];
incWithWeight<T, IT, WT>(estimation, weights_sum, weight, p);
}
modules/photo/src/fast_nlmeans_denoising_invoker_commons.hpp
+1 -1
View File
@@ -387,7 +387,7 @@ template <typename ET, typename IT, typename EW> struct incWithWeight_<Vec<ET, 4
};
template <typename T, typename IT, typename WT>
static inline void incWithWeight(IT* estimation, IT* weights_sum, IT weight, T p)
static inline void incWithWeight(IT* estimation, IT* weights_sum, WT weight, T p)
{
return incWithWeight_<T, IT, WT>::f(estimation, weights_sum, weight, p);
}
modules/photo/src/fast_nlmeans_multi_denoising_invoker.hpp
+1 -1
View File
@@ -262,7 +262,7 @@ void FastNlMeansMultiDenoisingInvoker<T, IT, UIT, D, WT>::operator() (const Rang
{
int almostAvgDist = dist_sums_row[x] >> almost_template_window_size_sq_bin_shift;
int weight = almost_dist2weight[almostAvgDist];
WT weight = almost_dist2weight[almostAvgDist];
T p = cur_row_ptr[border_size_ + search_window_x + x];
incWithWeight<T, IT, WT>(estimation, weights_sum, weight, p);
}
modules/photo/src/opencl/nlmeans.cl
+1 -1
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@@ -36,7 +36,7 @@ __kernel void calcAlmostDist2Weight(__global wlut_t * almostDist2Weight, int alm
#endif
wlut_t weight = convert_wlut_t(fixedPointMult * (isnan(w) ? (w_t)1.0 : w));
almostDist2Weight[almostDist] =
weight < WEIGHT_THRESHOLD * fixedPointMult ? (wlut_t)0 : weight;
weight < (wlut_t)(WEIGHT_THRESHOLD * fixedPointMult) ? (wlut_t)0 : weight;
}
}