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imageDenoising_nlm2_kernel.cuh
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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions 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.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER 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.
*/
////////////////////////////////////////////////////////////////////////////////
// 0 1 2 3 4 5 6 7
// 0 + . . . . . . .
// 1 . . . . . . . .
// 2 . . . . . . . .
// 3 . . . * . . . .
// 4 . . . . . . . .
// 5 . . . . . . . .
// 6 . . . . . . . .
// 7 . . . . . . . .
//
// * - Base point for every thread, + - pixel around which ColorDistance is
// computed
// The idea behind this method:
// - Every thread in a 8x8 block computes just one ColorDistance
// - It is saved in the weights array that is shared across the threads
// - Threads are synced
// - For every pixel inside the block weights are considered to be constants
////////////////////////////////////////////////////////////////////////////////
#include <cooperative_groups.h>
namespace cg = cooperative_groups;
__global__ void NLM2(TColor *dst, int imageW, int imageH, float Noise,
float lerpC, cudaTextureObject_t texImage) {
// Handle to thread block group
cg::thread_block cta = cg::this_thread_block();
// Weights cache
__shared__ float fWeights[BLOCKDIM_X * BLOCKDIM_Y];
const int ix = blockDim.x * blockIdx.x + threadIdx.x;
const int iy = blockDim.y * blockIdx.y + threadIdx.y;
// Add half of a texel to always address exact texel centers
const float x = (float)ix + 0.5f;
const float y = (float)iy + 0.5f;
const float cx = blockDim.x * blockIdx.x + NLM_WINDOW_RADIUS + 0.5f;
const float cy = blockDim.x * blockIdx.y + NLM_WINDOW_RADIUS + 0.5f;
if (ix < imageW && iy < imageH) {
// Find color distance from current texel to the center of NLM window
float weight = 0;
for (float n = -NLM_BLOCK_RADIUS; n <= NLM_BLOCK_RADIUS; n++)
for (float m = -NLM_BLOCK_RADIUS; m <= NLM_BLOCK_RADIUS; m++)
weight += vecLen(tex2D<float4>(texImage, cx + m, cy + n),
tex2D<float4>(texImage, x + m, y + n));
// Geometric distance from current texel to the center of NLM window
float dist =
(threadIdx.x - NLM_WINDOW_RADIUS) * (threadIdx.x - NLM_WINDOW_RADIUS) +
(threadIdx.y - NLM_WINDOW_RADIUS) * (threadIdx.y - NLM_WINDOW_RADIUS);
// Derive final weight from color and geometric distance
weight = __expf(-(weight * Noise + dist * INV_NLM_WINDOW_AREA));
// Write the result to shared memory
fWeights[threadIdx.y * BLOCKDIM_X + threadIdx.x] = weight;
// Wait until all the weights are ready
cg::sync(cta);
// Normalized counter for the NLM weight threshold
float fCount = 0;
// Total sum of pixel weights
float sumWeights = 0;
// Result accumulator
float3 clr = {0, 0, 0};
int idx = 0;
// Cycle through NLM window, surrounding (x, y) texel
for (float i = -NLM_WINDOW_RADIUS; i <= NLM_WINDOW_RADIUS + 1; i++)
for (float j = -NLM_WINDOW_RADIUS; j <= NLM_WINDOW_RADIUS + 1; j++) {
// Load precomputed weight
float weightIJ = fWeights[idx++];
// Accumulate (x + j, y + i) texel color with computed weight
float4 clrIJ = tex2D<float4>(texImage, x + j, y + i);
clr.x += clrIJ.x * weightIJ;
clr.y += clrIJ.y * weightIJ;
clr.z += clrIJ.z * weightIJ;
// Sum of weights for color normalization to [0..1] range
sumWeights += weightIJ;
// Update weight counter, if NLM weight for current window texel
// exceeds the weight threshold
fCount += (weightIJ > NLM_WEIGHT_THRESHOLD) ? INV_NLM_WINDOW_AREA : 0;
}
// Normalize result color by sum of weights
sumWeights = 1.0f / sumWeights;
clr.x *= sumWeights;
clr.y *= sumWeights;
clr.z *= sumWeights;
// Choose LERP quotient basing on how many texels
// within the NLM window exceeded the weight threshold
float lerpQ = (fCount > NLM_LERP_THRESHOLD) ? lerpC : 1.0f - lerpC;
// Write final result to global memory
float4 clr00 = tex2D<float4>(texImage, x, y);
clr.x = lerpf(clr.x, clr00.x, lerpQ);
clr.y = lerpf(clr.y, clr00.y, lerpQ);
clr.z = lerpf(clr.z, clr00.z, lerpQ);
dst[imageW * iy + ix] = make_color(clr.x, clr.y, clr.z, 0);
}
}
extern "C" void cuda_NLM2(TColor *d_dst, int imageW, int imageH, float Noise,
float LerpC, cudaTextureObject_t texImage) {
dim3 threads(BLOCKDIM_X, BLOCKDIM_Y);
dim3 grid(iDivUp(imageW, BLOCKDIM_X), iDivUp(imageH, BLOCKDIM_Y));
NLM2<<<grid, threads>>>(d_dst, imageW, imageH, Noise, LerpC, texImage);
}
////////////////////////////////////////////////////////////////////////////////
// Stripped NLM2 kernel, only highlighting areas with different LERP directions
////////////////////////////////////////////////////////////////////////////////
__global__ void NLM2diag(TColor *dst, int imageW, int imageH, float Noise,
float LerpC, cudaTextureObject_t texImage) {
// Handle to thread block group
cg::thread_block cta = cg::this_thread_block();
// Weights cache
__shared__ float fWeights[BLOCKDIM_X * BLOCKDIM_Y];
const int ix = blockDim.x * blockIdx.x + threadIdx.x;
const int iy = blockDim.y * blockIdx.y + threadIdx.y;
// Add half of a texel to always address exact texel centers
const float x = (float)ix + 0.5f;
const float y = (float)iy + 0.5f;
const float cx = blockDim.x * blockIdx.x + NLM_WINDOW_RADIUS + 0.5f;
const float cy = blockDim.x * blockIdx.y + NLM_WINDOW_RADIUS + 0.5f;
if (ix < imageW && iy < imageH) {
// Find color distance from current texel to the center of NLM window
float weight = 0;
for (float n = -NLM_BLOCK_RADIUS; n <= NLM_BLOCK_RADIUS + 1; n++)
for (float m = -NLM_BLOCK_RADIUS; m <= NLM_BLOCK_RADIUS + 1; m++)
weight += vecLen(tex2D<float4>(texImage, cx + m, cy + n),
tex2D<float4>(texImage, x + m, y + n));
// Geometric distance from current texel to the center of NLM window
float dist =
(threadIdx.x - NLM_WINDOW_RADIUS) * (threadIdx.x - NLM_WINDOW_RADIUS) +
(threadIdx.y - NLM_WINDOW_RADIUS) * (threadIdx.y - NLM_WINDOW_RADIUS);
// Derive final weight from color and geometric distance
weight = __expf(-(weight * Noise + dist * INV_NLM_WINDOW_AREA));
// Write the result to shared memory
fWeights[threadIdx.y * BLOCKDIM_X + threadIdx.x] = weight;
// Wait until all the weights are ready
cg::sync(cta);
// Normalized counter for the NLM weight threshold
float fCount = 0;
int idx = 0;
// Cycle through NLM window, surrounding (x, y) texel
for (float n = -NLM_WINDOW_RADIUS; n <= NLM_WINDOW_RADIUS + 1; n++)
for (float m = -NLM_WINDOW_RADIUS; m <= NLM_WINDOW_RADIUS + 1; m++) {
// Load precomputed weight
float weightIJ = fWeights[idx++];
// Update weight counter, if NLM weight for current window texel
// exceeds the weight threshold
fCount += (weightIJ > NLM_WEIGHT_THRESHOLD) ? INV_NLM_WINDOW_AREA : 0;
}
// Choose LERP quotient basing on how many texels
// within the NLM window exceeded the weight threshold
float lerpQ = (fCount > NLM_LERP_THRESHOLD) ? 1.0f : 0.0f;
// Write final result to global memory
dst[imageW * iy + ix] = make_color(lerpQ, 0, (1.0f - lerpQ), 0);
};
}
extern "C" void cuda_NLM2diag(TColor *d_dst, int imageW, int imageH,
float Noise, float LerpC,
cudaTextureObject_t texImage) {
dim3 threads(BLOCKDIM_X, BLOCKDIM_Y);
dim3 grid(iDivUp(imageW, BLOCKDIM_X), iDivUp(imageH, BLOCKDIM_Y));
NLM2diag<<<grid, threads>>>(d_dst, imageW, imageH, Noise, LerpC, texImage);
}