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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
#include "precomp.hpp"
#ifndef __OPENCV_FAST_NLMEANS_DENOISING_OPENCL_HPP__
#define __OPENCV_FAST_NLMEANS_DENOISING_OPENCL_HPP__
#include "opencl_kernels_photo.hpp"
#ifdef HAVE_OPENCL
namespace cv {
enum
{
BLOCK_ROWS = 32,
BLOCK_COLS = 32,
CTA_SIZE_INTEL = 64,
CTA_SIZE_DEFAULT = 256
};
static int divUp(int a, int b)
{
return (a + b - 1) / b;
}
template <typename FT>
static bool ocl_calcAlmostDist2Weight(UMat & almostDist2Weight, int searchWindowSize, int templateWindowSize, FT h, int cn,
int & almostTemplateWindowSizeSqBinShift)
{
const int maxEstimateSumValue = searchWindowSize * searchWindowSize * 255;
int fixedPointMult = std::numeric_limits<int>::max() / maxEstimateSumValue;
int depth = DataType<FT>::depth;
bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
if (depth == CV_64F && !doubleSupport)
return false;
// precalc weight for every possible l2 dist between blocks
// additional optimization of precalced weights to replace division(averaging) by binary shift
CV_Assert(templateWindowSize <= 46340); // sqrt(INT_MAX)
int templateWindowSizeSq = templateWindowSize * templateWindowSize;
almostTemplateWindowSizeSqBinShift = getNearestPowerOf2(templateWindowSizeSq);
FT almostDist2ActualDistMultiplier = (FT)(1 << almostTemplateWindowSizeSqBinShift) / templateWindowSizeSq;
const FT WEIGHT_THRESHOLD = 1e-3f;
int maxDist = 255 * 255 * cn;
int almostMaxDist = (int)(maxDist / almostDist2ActualDistMultiplier + 1);
FT den = 1.0f / (h * h * cn);
almostDist2Weight.create(1, almostMaxDist, CV_32SC1);
ocl::Kernel k("calcAlmostDist2Weight", ocl::photo::nlmeans_oclsrc,
format("-D OP_CALC_WEIGHTS -D FT=%s%s", ocl::typeToStr(depth),
doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
if (k.empty())
return false;
k.args(ocl::KernelArg::PtrWriteOnly(almostDist2Weight), almostMaxDist,
almostDist2ActualDistMultiplier, fixedPointMult, den, WEIGHT_THRESHOLD);
size_t globalsize[1] = { almostMaxDist };
return k.run(1, globalsize, NULL, false);
}
static bool ocl_fastNlMeansDenoising(InputArray _src, OutputArray _dst, float h,
int templateWindowSize, int searchWindowSize)
{
int type = _src.type(), cn = CV_MAT_CN(type);
int ctaSize = ocl::Device::getDefault().isIntel() ? CTA_SIZE_INTEL : CTA_SIZE_DEFAULT;
Size size = _src.size();
if ( type != CV_8UC1 && type != CV_8UC2 && type != CV_8UC4 )
return false;
int templateWindowHalfWize = templateWindowSize / 2;
int searchWindowHalfSize = searchWindowSize / 2;
templateWindowSize = templateWindowHalfWize * 2 + 1;
searchWindowSize = searchWindowHalfSize * 2 + 1;
int nblocksx = divUp(size.width, BLOCK_COLS), nblocksy = divUp(size.height, BLOCK_ROWS);
int almostTemplateWindowSizeSqBinShift = -1;
char cvt[2][40];
String opts = format("-D OP_CALC_FASTNLMEANS -D TEMPLATE_SIZE=%d -D SEARCH_SIZE=%d"
" -D uchar_t=%s -D int_t=%s -D BLOCK_COLS=%d -D BLOCK_ROWS=%d"
" -D CTA_SIZE=%d -D TEMPLATE_SIZE2=%d -D SEARCH_SIZE2=%d"
" -D convert_int_t=%s -D cn=%d -D convert_uchar_t=%s",
templateWindowSize, searchWindowSize, ocl::typeToStr(type),
ocl::typeToStr(CV_32SC(cn)), BLOCK_COLS, BLOCK_ROWS, ctaSize,
templateWindowHalfWize, searchWindowHalfSize,
ocl::convertTypeStr(CV_8U, CV_32S, cn, cvt[0]), cn,
ocl::convertTypeStr(CV_32S, CV_8U, cn, cvt[1]));
ocl::Kernel k("fastNlMeansDenoising", ocl::photo::nlmeans_oclsrc, opts);
if (k.empty())
return false;
UMat almostDist2Weight;
if (!ocl_calcAlmostDist2Weight<float>(almostDist2Weight, searchWindowSize, templateWindowSize, h, cn,
almostTemplateWindowSizeSqBinShift))
return false;
CV_Assert(almostTemplateWindowSizeSqBinShift >= 0);
UMat srcex;
int borderSize = searchWindowHalfSize + templateWindowHalfWize;
copyMakeBorder(_src, srcex, borderSize, borderSize, borderSize, borderSize, BORDER_DEFAULT);
_dst.create(size, type);
UMat dst = _dst.getUMat();
int searchWindowSizeSq = searchWindowSize * searchWindowSize;
Size upColSumSize(size.width, searchWindowSizeSq * nblocksy);
Size colSumSize(nblocksx * templateWindowSize, searchWindowSizeSq * nblocksy);
UMat buffer(upColSumSize + colSumSize, CV_32SC(cn));
srcex = srcex(Rect(Point(borderSize, borderSize), size));
k.args(ocl::KernelArg::ReadOnlyNoSize(srcex), ocl::KernelArg::WriteOnly(dst),
ocl::KernelArg::PtrReadOnly(almostDist2Weight),
ocl::KernelArg::PtrReadOnly(buffer), almostTemplateWindowSizeSqBinShift);
size_t globalsize[2] = { nblocksx * ctaSize, nblocksy }, localsize[2] = { ctaSize, 1 };
return k.run(2, globalsize, localsize, false);
}
static bool ocl_fastNlMeansDenoisingColored( InputArray _src, OutputArray _dst,
float h, float hForColorComponents,
int templateWindowSize, int searchWindowSize)
{
UMat src = _src.getUMat();
_dst.create(src.size(), src.type());
UMat dst = _dst.getUMat();
UMat src_lab;
cvtColor(src, src_lab, COLOR_LBGR2Lab);
UMat l(src.size(), CV_8U);
UMat ab(src.size(), CV_8UC2);
std::vector<UMat> l_ab(2), l_ab_denoised(2);
l_ab[0] = l;
l_ab[1] = ab;
l_ab_denoised[0].create(src.size(), CV_8U);
l_ab_denoised[1].create(src.size(), CV_8UC2);
int from_to[] = { 0,0, 1,1, 2,2 };
mixChannels(std::vector<UMat>(1, src_lab), l_ab, from_to, 3);
fastNlMeansDenoising(l_ab[0], l_ab_denoised[0], h, templateWindowSize, searchWindowSize);
fastNlMeansDenoising(l_ab[1], l_ab_denoised[1], hForColorComponents, templateWindowSize, searchWindowSize);
UMat dst_lab(src.size(), CV_8UC3);
mixChannels(l_ab_denoised, std::vector<UMat>(1, dst_lab), from_to, 3);
cvtColor(dst_lab, dst, COLOR_Lab2LBGR, src.channels());
return true;
}
}
#endif
#endif