文件列表:

Makefile (591, 2021-04-15)
benchmark.sh (574, 2021-04-15)
data (0, 2021-04-15)
data\images (0, 2021-04-15)
data\images\noisy_flower.png (31899, 2021-04-15)
data\images\noisy_house.png (13726, 2021-04-15)
data\images\noisy_lena.png (81259, 2021-04-15)
data\images\original_flower.png (19288, 2021-04-15)
data\images\original_house.png (12075, 2021-04-15)
data\images\original_lena.png (45905, 2021-04-15)
data\in (0, 2021-04-15)
data\in\noisy_flower.txt (118938, 2021-04-15)
data\in\noisy_house.txt (32234, 2021-04-15)
data\in\noisy_lena.txt (506202, 2021-04-15)
data\standard (0, 2021-04-15)
data\standard\cuda_standard_5_0.06_0.8.txt (36928, 2021-04-15)
data\standard\cuda_standard_res_5_0.06_0.8.txt (38923, 2021-04-15)
data\standard\house.txt (32535, 2021-04-15)
data\standard\standard_5_0.06_0.8.txt (36928, 2021-04-15)
data\standard\standard_res_5_0.06_0.8.txt (38923, 2021-04-15)
include (0, 2021-04-15)
include\cudaFilteringGlobalMem.cuh (2677, 2021-04-15)
include\cudaFilteringSharedMem.cuh (3120, 2021-04-15)
include\filtering.cuh (1895, 2021-04-15)
include\utils.cuh (9560, 2021-04-15)
matlab (0, 2021-04-15)
matlab\add_noise.m (373, 2021-04-15)
matlab\convert_jpg.m (103, 2021-04-15)
matlab\euclideanDistance.m (177, 2021-04-15)
matlab\export_txt.m (243, 2021-04-15)
matlab\flower.mat (34321, 2021-04-15)
matlab\flower.txt (118716, 2021-04-15)
matlab\house.mat (7981, 2021-04-15)
matlab\house.txt (32535, 2021-04-15)
matlab\image.mat (14377, 2021-04-15)
matlab\lena.mat (136967, 2021-04-15)
matlab\lena.txt (505894, 2021-04-15)
... ...

# Non Local Means - CUDA Implementation of **Non Local Means** algorithm for image denoising. * **version 1**: CPU sequential in C++ * **version 2**: GPU parallel in CUDA * **version 3**: GPU parallel using shared memory in CUDA ## Build instructions **Requierements:** nvcc (Nvidia CUDA Compiler) Set parameters in Makefile and ```bash make ``` or ```bash mkdir -p data/out nvcc -o build/main -I./include src/main.cu -O3 ``` and run with ```bash ./build/main $(imageNum) $(patchSize) $(filterSigma) $(patchSigma) $(useGpu) $(useSharedMem) ``` ## Instructions to see the filtered images Run the script `matlab/show_image.m` in MATLAB and all the output images of folder `data/out` will show up. Original and noisy images can be found in `data/images`.

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