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218 lines
8.9 KiB
Plaintext
218 lines
8.9 KiB
Plaintext
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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////////////////////////////////////////////////////////////////////////////////
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// 0 1 2 3 4 5 6 7
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// 0 + . . . . . . .
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// 1 . . . . . . . .
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// 2 . . . . . . . .
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// 3 . . . * . . . .
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// 4 . . . . . . . .
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// 5 . . . . . . . .
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// 6 . . . . . . . .
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// 7 . . . . . . . .
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//
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// * - Base point for every thread, + - pixel around which ColorDistance is
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// computed
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// The idea behind this method:
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// - Every thread in a 8x8 block computes just one ColorDistance
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// - It is saved in the weights array that is shared across the threads
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// - Threads are synced
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// - For every pixel inside the block weights are considered to be constants
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////////////////////////////////////////////////////////////////////////////////
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#include <cooperative_groups.h>
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namespace cg = cooperative_groups;
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__global__ void NLM2(TColor *dst, int imageW, int imageH, float Noise,
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float lerpC, cudaTextureObject_t texImage) {
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// Handle to thread block group
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cg::thread_block cta = cg::this_thread_block();
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// Weights cache
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__shared__ float fWeights[BLOCKDIM_X * BLOCKDIM_Y];
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const int ix = blockDim.x * blockIdx.x + threadIdx.x;
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const int iy = blockDim.y * blockIdx.y + threadIdx.y;
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// Add half of a texel to always address exact texel centers
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const float x = (float)ix + 0.5f;
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const float y = (float)iy + 0.5f;
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const float cx = blockDim.x * blockIdx.x + NLM_WINDOW_RADIUS + 0.5f;
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const float cy = blockDim.x * blockIdx.y + NLM_WINDOW_RADIUS + 0.5f;
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if (ix < imageW && iy < imageH) {
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// Find color distance from current texel to the center of NLM window
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float weight = 0;
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for (float n = -NLM_BLOCK_RADIUS; n <= NLM_BLOCK_RADIUS; n++)
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for (float m = -NLM_BLOCK_RADIUS; m <= NLM_BLOCK_RADIUS; m++)
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weight += vecLen(tex2D<float4>(texImage, cx + m, cy + n),
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tex2D<float4>(texImage, x + m, y + n));
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// Geometric distance from current texel to the center of NLM window
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float dist =
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(threadIdx.x - NLM_WINDOW_RADIUS) * (threadIdx.x - NLM_WINDOW_RADIUS) +
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(threadIdx.y - NLM_WINDOW_RADIUS) * (threadIdx.y - NLM_WINDOW_RADIUS);
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// Derive final weight from color and geometric distance
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weight = __expf(-(weight * Noise + dist * INV_NLM_WINDOW_AREA));
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// Write the result to shared memory
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fWeights[threadIdx.y * BLOCKDIM_X + threadIdx.x] = weight;
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// Wait until all the weights are ready
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cg::sync(cta);
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// Normalized counter for the NLM weight threshold
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float fCount = 0;
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// Total sum of pixel weights
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float sumWeights = 0;
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// Result accumulator
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float3 clr = {0, 0, 0};
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int idx = 0;
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// Cycle through NLM window, surrounding (x, y) texel
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for (float i = -NLM_WINDOW_RADIUS; i <= NLM_WINDOW_RADIUS + 1; i++)
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for (float j = -NLM_WINDOW_RADIUS; j <= NLM_WINDOW_RADIUS + 1; j++) {
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// Load precomputed weight
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float weightIJ = fWeights[idx++];
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// Accumulate (x + j, y + i) texel color with computed weight
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float4 clrIJ = tex2D<float4>(texImage, x + j, y + i);
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clr.x += clrIJ.x * weightIJ;
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clr.y += clrIJ.y * weightIJ;
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clr.z += clrIJ.z * weightIJ;
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// Sum of weights for color normalization to [0..1] range
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sumWeights += weightIJ;
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// Update weight counter, if NLM weight for current window texel
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// exceeds the weight threshold
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fCount += (weightIJ > NLM_WEIGHT_THRESHOLD) ? INV_NLM_WINDOW_AREA : 0;
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}
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// Normalize result color by sum of weights
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sumWeights = 1.0f / sumWeights;
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clr.x *= sumWeights;
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clr.y *= sumWeights;
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clr.z *= sumWeights;
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// Choose LERP quotient basing on how many texels
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// within the NLM window exceeded the weight threshold
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float lerpQ = (fCount > NLM_LERP_THRESHOLD) ? lerpC : 1.0f - lerpC;
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// Write final result to global memory
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float4 clr00 = tex2D<float4>(texImage, x, y);
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clr.x = lerpf(clr.x, clr00.x, lerpQ);
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clr.y = lerpf(clr.y, clr00.y, lerpQ);
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clr.z = lerpf(clr.z, clr00.z, lerpQ);
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dst[imageW * iy + ix] = make_color(clr.x, clr.y, clr.z, 0);
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}
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}
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extern "C" void cuda_NLM2(TColor *d_dst, int imageW, int imageH, float Noise,
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float LerpC, cudaTextureObject_t texImage) {
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dim3 threads(BLOCKDIM_X, BLOCKDIM_Y);
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dim3 grid(iDivUp(imageW, BLOCKDIM_X), iDivUp(imageH, BLOCKDIM_Y));
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NLM2<<<grid, threads>>>(d_dst, imageW, imageH, Noise, LerpC, texImage);
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}
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////////////////////////////////////////////////////////////////////////////////
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// Stripped NLM2 kernel, only highlighting areas with different LERP directions
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////////////////////////////////////////////////////////////////////////////////
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__global__ void NLM2diag(TColor *dst, int imageW, int imageH, float Noise,
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float LerpC, cudaTextureObject_t texImage) {
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// Handle to thread block group
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cg::thread_block cta = cg::this_thread_block();
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// Weights cache
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__shared__ float fWeights[BLOCKDIM_X * BLOCKDIM_Y];
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const int ix = blockDim.x * blockIdx.x + threadIdx.x;
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const int iy = blockDim.y * blockIdx.y + threadIdx.y;
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// Add half of a texel to always address exact texel centers
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const float x = (float)ix + 0.5f;
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const float y = (float)iy + 0.5f;
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const float cx = blockDim.x * blockIdx.x + NLM_WINDOW_RADIUS + 0.5f;
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const float cy = blockDim.x * blockIdx.y + NLM_WINDOW_RADIUS + 0.5f;
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if (ix < imageW && iy < imageH) {
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// Find color distance from current texel to the center of NLM window
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float weight = 0;
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for (float n = -NLM_BLOCK_RADIUS; n <= NLM_BLOCK_RADIUS + 1; n++)
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for (float m = -NLM_BLOCK_RADIUS; m <= NLM_BLOCK_RADIUS + 1; m++)
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weight += vecLen(tex2D<float4>(texImage, cx + m, cy + n),
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tex2D<float4>(texImage, x + m, y + n));
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// Geometric distance from current texel to the center of NLM window
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float dist =
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(threadIdx.x - NLM_WINDOW_RADIUS) * (threadIdx.x - NLM_WINDOW_RADIUS) +
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(threadIdx.y - NLM_WINDOW_RADIUS) * (threadIdx.y - NLM_WINDOW_RADIUS);
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// Derive final weight from color and geometric distance
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weight = __expf(-(weight * Noise + dist * INV_NLM_WINDOW_AREA));
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// Write the result to shared memory
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fWeights[threadIdx.y * BLOCKDIM_X + threadIdx.x] = weight;
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// Wait until all the weights are ready
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cg::sync(cta);
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// Normalized counter for the NLM weight threshold
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float fCount = 0;
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int idx = 0;
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// Cycle through NLM window, surrounding (x, y) texel
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for (float n = -NLM_WINDOW_RADIUS; n <= NLM_WINDOW_RADIUS + 1; n++)
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for (float m = -NLM_WINDOW_RADIUS; m <= NLM_WINDOW_RADIUS + 1; m++) {
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// Load precomputed weight
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float weightIJ = fWeights[idx++];
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// Update weight counter, if NLM weight for current window texel
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// exceeds the weight threshold
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fCount += (weightIJ > NLM_WEIGHT_THRESHOLD) ? INV_NLM_WINDOW_AREA : 0;
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}
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// Choose LERP quotient basing on how many texels
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// within the NLM window exceeded the weight threshold
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float lerpQ = (fCount > NLM_LERP_THRESHOLD) ? 1.0f : 0.0f;
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// Write final result to global memory
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dst[imageW * iy + ix] = make_color(lerpQ, 0, (1.0f - lerpQ), 0);
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};
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}
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extern "C" void cuda_NLM2diag(TColor *d_dst, int imageW, int imageH,
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float Noise, float LerpC,
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cudaTextureObject_t texImage) {
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dim3 threads(BLOCKDIM_X, BLOCKDIM_Y);
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dim3 grid(iDivUp(imageW, BLOCKDIM_X), iDivUp(imageH, BLOCKDIM_Y));
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NLM2diag<<<grid, threads>>>(d_dst, imageW, imageH, Noise, LerpC, texImage);
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}
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