mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2024-11-25 12:39:15 +08:00
154 lines
6.8 KiB
Plaintext
154 lines
6.8 KiB
Plaintext
/* 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.
|
|
*/
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// NLM kernel
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
__global__ void NLM(TColor *dst, int imageW, int imageH, float Noise,
|
|
float lerpC, cudaTextureObject_t texImage) {
|
|
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;
|
|
|
|
if (ix < imageW && iy < imageH) {
|
|
// 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};
|
|
|
|
// Cycle through NLM window, surrounding (x, y) texel
|
|
for (float i = -NLM_WINDOW_RADIUS; i <= NLM_WINDOW_RADIUS; i++)
|
|
for (float j = -NLM_WINDOW_RADIUS; j <= NLM_WINDOW_RADIUS; j++) {
|
|
// Find color distance from (x, y) to (x + j, y + i)
|
|
float weightIJ = 0;
|
|
|
|
for (float n = -NLM_BLOCK_RADIUS; n <= NLM_BLOCK_RADIUS; n++)
|
|
for (float m = -NLM_BLOCK_RADIUS; m <= NLM_BLOCK_RADIUS; m++)
|
|
weightIJ += vecLen(tex2D<float4>(texImage, x + j + m, y + i + n),
|
|
tex2D<float4>(texImage, x + m, y + n));
|
|
|
|
// Derive final weight from color and geometric distance
|
|
weightIJ =
|
|
__expf(-(weightIJ * Noise + (i * i + j * j) * INV_NLM_WINDOW_AREA));
|
|
|
|
// 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_NLM(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));
|
|
|
|
NLM<<<grid, threads>>>(d_dst, imageW, imageH, Noise, lerpC, texImage);
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// Stripped NLM kernel, only highlighting areas with different LERP directions
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
__global__ void NLMdiag(TColor *dst, unsigned int imageW, unsigned int imageH,
|
|
float Noise, float lerpC,
|
|
cudaTextureObject_t texImage) {
|
|
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;
|
|
|
|
if (ix < imageW && iy < imageH) {
|
|
// Normalized counter for the weight threshold
|
|
float fCount = 0;
|
|
|
|
// Cycle through NLM window, surrounding (x, y) texel
|
|
for (float i = -NLM_WINDOW_RADIUS; i <= NLM_WINDOW_RADIUS; i++)
|
|
for (float j = -NLM_WINDOW_RADIUS; j <= NLM_WINDOW_RADIUS; j++) {
|
|
// Find color distance between (x, y) and (x + j, y + i)
|
|
float weightIJ = 0;
|
|
|
|
for (float n = -NLM_BLOCK_RADIUS; n <= NLM_BLOCK_RADIUS; n++)
|
|
for (float m = -NLM_BLOCK_RADIUS; m <= NLM_BLOCK_RADIUS; m++)
|
|
weightIJ += vecLen(tex2D<float4>(texImage, x + j + m, y + i + n),
|
|
tex2D<float4>(texImage, x + m, y + n));
|
|
|
|
// Derive final weight from color and geometric distance
|
|
weightIJ =
|
|
__expf(-(weightIJ * Noise + (i * i + j * j) * INV_NLM_WINDOW_AREA));
|
|
|
|
// Increase the weight threshold counter
|
|
fCount += (weightIJ > NLM_WEIGHT_THRESHOLD) ? INV_NLM_WINDOW_AREA : 0;
|
|
}
|
|
|
|
// Choose LERP quotient basing on how many texels
|
|
// within the NLM window exceeded the LERP threshold
|
|
float lerpQ = (fCount > NLM_LERP_THRESHOLD) ? 1.0f : 0;
|
|
|
|
// Write final result to global memory
|
|
dst[imageW * iy + ix] = make_color(lerpQ, 0, (1.0f - lerpQ), 0);
|
|
};
|
|
}
|
|
|
|
extern "C" void cuda_NLMdiag(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));
|
|
|
|
NLMdiag<<<grid, threads>>>(d_dst, imageW, imageH, Noise, lerpC, texImage);
|
|
}
|