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| -rw-r--r-- | Wrappers/Matlab/demos/demoMatlab_denoise.m~ | 31 |
1 files changed, 0 insertions, 31 deletions
diff --git a/Wrappers/Matlab/demos/demoMatlab_denoise.m~ b/Wrappers/Matlab/demos/demoMatlab_denoise.m~ deleted file mode 100644 index 3f4403e..0000000 --- a/Wrappers/Matlab/demos/demoMatlab_denoise.m~ +++ /dev/null @@ -1,31 +0,0 @@ -% Image (2D) denoising demo using CCPi-RGL - -addpath('../mex_compile/installed'); -addpath('../../../data/'); - -Im = double(imread('lena_gray_256.tif'))/255; % loading image -u0 = Im + .05*randn(size(Im)); u0(u0 < 0) = 0; -figure; imshow(u0, [0 1]); title('Noisy image'); - -%% -fprintf('Denoise using ROF-TV model (CPU) \n'); -lambda_rof = 0.02; % regularization parameter -tau_rof = 0.0025; % time-marching constant -iter_rof = 2000; % number of ROF iterations -tic; u_rof = ROF_TV(single(u0), lambda_rof, iter_rof, tau_rof); toc; -figure; imshow(u_rof, [0 1]); title('ROF-TV denoised image (CPU)'); -%% -% fprintf('Denoise using ROF-TV model (GPU) \n'); -% lambda_rof = 0.02; % regularization parameter -% tau_rof = 0.0025; % time-marching constant -% iter_rof = 2000; % number of ROF iterations -% tic; u_rof = ROF_TV_GPU(single(u0), lambda_rof, iter_rof, tau_rof); toc; -% figure; imshow(u_rof, [0 1]); title('ROF-TV denoised image (GPU)'); -%% -fprintf('Denoise using FGP-TV model (CPU) \n'); -lambda_fgp = 0.02; % regularization parameter -iter_fgp = 2000; % number of FGP iterations -epsil_tol = 1.0e-05; % tolerance -tic; u_fgp = FGP_TV(single(u0), lambda_fgp, iter_fgp, epsil_tol); toc; -figure; imshow(u_rof, [0 1]); title('ROF-TV denoised image (CPU)'); -%%
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