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| author | Daniil Kazantsev <dkazanc3@googlemail.com> | 2018-12-04 16:18:38 +0000 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2018-12-04 16:18:38 +0000 |
| commit | b6140c987875ff415b225f8800c4b582295db654 (patch) | |
| tree | 5074abd308c3e2f4425ee27251d242f3273f1dd4 /Wrappers/Matlab/demos | |
| parent | 8b8dfc68fa6b70ec7eefcdfb928fb383196bec97 (diff) | |
| parent | c9ee9ecc84881595b04f19280c93bcd587171270 (diff) | |
| download | regularization-b6140c987875ff415b225f8800c4b582295db654.tar.gz regularization-b6140c987875ff415b225f8800c4b582295db654.tar.bz2 regularization-b6140c987875ff415b225f8800c4b582295db654.tar.xz regularization-b6140c987875ff415b225f8800c4b582295db654.zip | |
Merge pull request #77 from vais-ral/nltv_gpu
NLTV for GPU
Diffstat (limited to 'Wrappers/Matlab/demos')
| -rw-r--r-- | Wrappers/Matlab/demos/demoMatlab_denoise.m | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/Wrappers/Matlab/demos/demoMatlab_denoise.m b/Wrappers/Matlab/demos/demoMatlab_denoise.m index 54b8bac..3506cca 100644 --- a/Wrappers/Matlab/demos/demoMatlab_denoise.m +++ b/Wrappers/Matlab/demos/demoMatlab_denoise.m @@ -138,17 +138,17 @@ figure; imshow(u_diff4, [0 1]); title('Diffusion 4thO denoised image (CPU)'); fprintf('Weights pre-calculation for Non-local TV (takes time on CPU) \n'); SearchingWindow = 7; PatchWindow = 2; -NeighboursNumber = 15; % the number of neibours to include +NeighboursNumber = 20; % the number of neibours to include h = 0.23; % edge related parameter for NLM -[H_i, H_j, Weights] = PatchSelect(single(u0), SearchingWindow, PatchWindow, NeighboursNumber, h); +tic; [H_i, H_j, Weights] = PatchSelect(single(u0), SearchingWindow, PatchWindow, NeighboursNumber, h); toc; %% fprintf('Denoise using Non-local Total Variation (CPU) \n'); -iter_nltv = 2; % number of nltv iterations -lambda_nltv = 0.085; % regularisation parameter for nltv +iter_nltv = 3; % number of nltv iterations +lambda_nltv = 0.05; % regularisation parameter for nltv tic; u_nltv = Nonlocal_TV(single(u0), H_i, H_j, 0, Weights, lambda_nltv, iter_nltv); toc; rmse_nltv = (RMSE(u_nltv(:),Im(:))); fprintf('%s %f \n', 'RMSE error for Non-local Total Variation is:', rmse_nltv); -figure; imshow(u_nltv, [0 1]); title('Non-local Total Variation denoised image (CPU)'); +figure; imagesc(u_nltv, [0 1]); colormap(gray); daspect([1 1 1]); title('Non-local Total Variation denoised image (CPU)'); %% %>>>>>>>>>>>>>> MULTI-CHANNEL priors <<<<<<<<<<<<<<< % |