+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+// By downloading, copying, installing or using the software you agree to this license.
+// If you do not agree to this license, do not download, install,
+// copy or use the software.
+//
+//
+// License Agreement
+// For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 1993-2011, NVIDIA Corporation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+// * Redistribution's of source code must retain the above copyright notice,
+// this list of conditions and the following disclaimer.
+//
+// * Redistribution's in binary form must reproduce the above copyright notice,
+// this list of conditions and the following disclaimer in the documentation
+// and/or other materials provided with the distribution.
+//
+// * The name of the copyright holders may not be used to endorse or promote products
+// derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or bpied warranties, including, but not limited to, the bpied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "internal_shared.hpp"
+
+#include "opencv2/gpu/device/vec_traits.hpp"
+#include "opencv2/gpu/device/vec_math.hpp"
+#include "opencv2/gpu/device/border_interpolate.hpp"
+
+using namespace cv::gpu;
+
+typedef unsigned char uchar;
+typedef unsigned short ushort;
+
+//////////////////////////////////////////////////////////////////////////////////
+/// Non local means denosings
+
+namespace cv { namespace gpu { namespace device
+{
+ namespace imgproc
+ {
+ __device__ __forceinline__ float norm2(const float& v) { return v*v; }
+ __device__ __forceinline__ float norm2(const float2& v) { return v.x*v.x + v.y*v.y; }
+ __device__ __forceinline__ float norm2(const float3& v) { return v.x*v.x + v.y*v.y + v.z*v.z; }
+ __device__ __forceinline__ float norm2(const float4& v) { return v.x*v.x + v.y*v.y + v.z*v.z + v.w*v.w; }
+
+ template<typename T, typename B>
+ __global__ void nlm_kernel(const PtrStepSz<T> src, PtrStep<T> dst, const B b, int search_radius, int block_radius, float h2_inv_half)
+ {
+ typedef typename TypeVec<float, VecTraits<T>::cn>::vec_type value_type;
+
+ const int x = blockDim.x * blockIdx.x + threadIdx.x;
+ const int y = blockDim.y * blockIdx.y + threadIdx.y;
+
+ if (x >= src.cols || y >= src.rows)
+ return;
+
+ float block_radius2_inv = -1.f/(block_radius * block_radius);
+
+ value_type sum1 = VecTraits<value_type>::all(0);
+ float sum2 = 0.f;
+
+ for(float cy = -search_radius; cy <= search_radius; ++cy)
+ for(float cx = -search_radius; cx <= search_radius; ++cx)
+ {
+ float color2 = 0;
+ for(float by = -block_radius; by <= block_radius; ++by)
+ for(float bx = -block_radius; bx <= block_radius; ++bx)
+ {
+ value_type v1 = saturate_cast<value_type>(src(y + by, x + bx));
+ value_type v2 = saturate_cast<value_type>(src(y + cy + by, x + cx + bx));
+ color2 += norm2(v1 - v2);
+ }
+
+ float dist2 = cx * cx + cy * cy;
+ float w = __expf(color2 * h2_inv_half + dist2 * block_radius2_inv);
+
+ sum1 = sum1 + saturate_cast<value_type>(src(y + cy, x + cy)) * w;
+ sum2 += w;
+ }
+
+ dst(y, x) = saturate_cast<T>(sum1 / sum2);
+
+ }
+
+ template<typename T, template <typename> class B>
+ void nlm_caller(const PtrStepSzb src, PtrStepSzb dst, int search_radius, int block_radius, float h, cudaStream_t stream)
+ {
+ dim3 block (32, 8);
+ dim3 grid (divUp (src.cols, block.x), divUp (src.rows, block.y));
+
+ B<T> b(src.rows, src.cols);
+
+ float h2_inv_half = -0.5f/(h * h * VecTraits<T>::cn);
+
+ cudaSafeCall( cudaFuncSetCacheConfig (nlm_kernel<T, B<T> >, cudaFuncCachePreferL1) );
+ nlm_kernel<<<grid, block>>>((PtrStepSz<T>)src, (PtrStepSz<T>)dst, b, search_radius, block_radius, h2_inv_half);
+ cudaSafeCall ( cudaGetLastError () );
+
+ if (stream == 0)
+ cudaSafeCall( cudaDeviceSynchronize() );
+ }
+
+ template<typename T>
+ void nlm_bruteforce_gpu(const PtrStepSzb& src, PtrStepSzb dst, int search_radius, int block_radius, float h, int borderMode, cudaStream_t stream)
+ {
+ typedef void (*func_t)(const PtrStepSzb src, PtrStepSzb dst, int search_radius, int block_radius, float h, cudaStream_t stream);
+
+ static func_t funcs[] =
+ {
+ nlm_caller<T, BrdReflect101>,
+ nlm_caller<T, BrdReplicate>,
+ nlm_caller<T, BrdConstant>,
+ nlm_caller<T, BrdReflect>,
+ nlm_caller<T, BrdWrap>,
+ };
+ funcs[borderMode](src, dst, search_radius, block_radius, h, stream);
+ }
+
+ template void nlm_bruteforce_gpu<uchar>(const PtrStepSzb&, PtrStepSzb, int, int, float, int, cudaStream_t);
+ template void nlm_bruteforce_gpu<uchar3>(const PtrStepSzb&, PtrStepSzb, int, int, float, int, cudaStream_t);
+ }
+}}}