cuda-samples/Samples/2_Concepts_and_Techniques/imageDenoising/imageDenoising.cu
2022-01-13 11:35:24 +05:30

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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
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
* This sample demonstrates two adaptive image denoising techniques:
* KNN and NLM, based on computation of both geometric and color distance
* between texels. While both techniques are already implemented in the
* DirectX SDK using shaders, massively speeded up variation
* of the latter technique, taking advantage of shared memory, is implemented
* in addition to DirectX counterparts.
* See supplied whitepaper for more explanations.
*/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <helper_cuda.h>
#include "imageDenoising.h"
////////////////////////////////////////////////////////////////////////////////
// Helper functions
////////////////////////////////////////////////////////////////////////////////
float Max(float x, float y) { return (x > y) ? x : y; }
float Min(float x, float y) { return (x < y) ? x : y; }
int iDivUp(int a, int b) { return ((a % b) != 0) ? (a / b + 1) : (a / b); }
__device__ float lerpf(float a, float b, float c) { return a + (b - a) * c; }
__device__ float vecLen(float4 a, float4 b) {
return ((b.x - a.x) * (b.x - a.x) + (b.y - a.y) * (b.y - a.y) +
(b.z - a.z) * (b.z - a.z));
}
__device__ TColor make_color(float r, float g, float b, float a) {
return ((int)(a * 255.0f) << 24) | ((int)(b * 255.0f) << 16) |
((int)(g * 255.0f) << 8) | ((int)(r * 255.0f) << 0);
}
////////////////////////////////////////////////////////////////////////////////
// Global data handlers and parameters
////////////////////////////////////////////////////////////////////////////////
// Texture object and channel descriptor for image texture
cudaTextureObject_t texImage;
cudaChannelFormatDesc uchar4tex = cudaCreateChannelDesc<uchar4>();
// CUDA array descriptor
cudaArray *a_Src;
////////////////////////////////////////////////////////////////////////////////
// Filtering kernels
////////////////////////////////////////////////////////////////////////////////
#include "imageDenoising_copy_kernel.cuh"
#include "imageDenoising_knn_kernel.cuh"
#include "imageDenoising_nlm_kernel.cuh"
#include "imageDenoising_nlm2_kernel.cuh"
extern "C" cudaError_t CUDA_MallocArray(uchar4 **h_Src, int imageW,
int imageH) {
cudaError_t error;
error = cudaMallocArray(&a_Src, &uchar4tex, imageW, imageH);
error = cudaMemcpy2DToArray(a_Src, 0, 0, *h_Src, sizeof(uchar4) * imageW,
sizeof(uchar4) * imageW, imageH,
cudaMemcpyHostToDevice);
cudaResourceDesc texRes;
memset(&texRes, 0, sizeof(cudaResourceDesc));
texRes.resType = cudaResourceTypeArray;
texRes.res.array.array = a_Src;
cudaTextureDesc texDescr;
memset(&texDescr, 0, sizeof(cudaTextureDesc));
texDescr.normalizedCoords = false;
texDescr.filterMode = cudaFilterModeLinear;
texDescr.addressMode[0] = cudaAddressModeWrap;
texDescr.addressMode[1] = cudaAddressModeWrap;
texDescr.readMode = cudaReadModeNormalizedFloat;
checkCudaErrors(cudaCreateTextureObject(&texImage, &texRes, &texDescr, NULL));
return error;
}
extern "C" cudaError_t CUDA_FreeArray() { return cudaFreeArray(a_Src); }