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| author | Daniil Kazantsev <dkazanc@hotmail.com> | 2018-05-04 09:57:09 +0100 |
|---|---|---|
| committer | Daniil Kazantsev <dkazanc@hotmail.com> | 2018-05-04 09:57:09 +0100 |
| commit | fd62af62943acf481960eebbe9e986a620e6ebc9 (patch) | |
| tree | 91c025c65bf810c86d0eb918b610306f0924f35d | |
| parent | 824fafc9d39bfd3a27ffdb29c37f873e6097c3f7 (diff) | |
| download | regularization-fd62af62943acf481960eebbe9e986a620e6ebc9.tar.gz regularization-fd62af62943acf481960eebbe9e986a620e6ebc9.tar.bz2 regularization-fd62af62943acf481960eebbe9e986a620e6ebc9.tar.xz regularization-fd62af62943acf481960eebbe9e986a620e6ebc9.zip | |
corrections to demos
| -rw-r--r-- | Wrappers/Matlab/demos/demoMatlab_3Ddenoise.m | 9 | ||||
| -rw-r--r-- | Wrappers/Matlab/demos/demoMatlab_denoise.m | 4 |
2 files changed, 6 insertions, 7 deletions
diff --git a/Wrappers/Matlab/demos/demoMatlab_3Ddenoise.m b/Wrappers/Matlab/demos/demoMatlab_3Ddenoise.m index 33dfb95..9a65e37 100644 --- a/Wrappers/Matlab/demos/demoMatlab_3Ddenoise.m +++ b/Wrappers/Matlab/demos/demoMatlab_3Ddenoise.m @@ -57,19 +57,18 @@ figure; imshow(u_sb(:,:,15), [0 1]); title('SB-TV denoised volume (CPU)'); % tic; u_sbG = SB_TV_GPU(single(vol3D), lambda_reg, iter_sb, epsil_tol); toc; % figure; imshow(u_sbG(:,:,15), [0 1]); title('SB-TV denoised volume (GPU)'); %% -%% fprintf('Denoise a volume using Nonlinear-Diffusion model (CPU) \n'); iter_diff = 300; % number of diffusion iterations -lambda_regDiff = 0.06; % regularisation for the diffusivity -sigmaPar = 0.04; % edge-preserving parameter +lambda_regDiff = 0.025; % regularisation for the diffusivity +sigmaPar = 0.015; % edge-preserving parameter tau_param = 0.025; % time-marching constant tic; u_diff = NonlDiff(single(vol3D), lambda_regDiff, sigmaPar, iter_diff, tau_param, 'Huber'); toc; figure; imshow(u_diff(:,:,15), [0 1]); title('Diffusion denoised volume (CPU)'); %% % fprintf('Denoise a volume using Nonlinear-Diffusion model (GPU) \n'); % iter_diff = 300; % number of diffusion iterations -% lambda_regDiff = 0.06; % regularisation for the diffusivity -% sigmaPar = 0.04; % edge-preserving parameter +% lambda_regDiff = 0.025; % regularisation for the diffusivity +% sigmaPar = 0.015; % edge-preserving parameter % tau_param = 0.025; % time-marching constant % tic; u_diff_g = NonlDiff_GPU(single(vol3D), lambda_regDiff, sigmaPar, iter_diff, tau_param, 'Huber'); toc; % figure; imshow(u_diff_g(:,:,15), [0 1]); title('Diffusion denoised volume (GPU)'); diff --git a/Wrappers/Matlab/demos/demoMatlab_denoise.m b/Wrappers/Matlab/demos/demoMatlab_denoise.m index df47bdc..8289f41 100644 --- a/Wrappers/Matlab/demos/demoMatlab_denoise.m +++ b/Wrappers/Matlab/demos/demoMatlab_denoise.m @@ -61,8 +61,8 @@ figure; imshow(u_diff, [0 1]); title('Diffusion denoised image (CPU)'); %% % fprintf('Denoise using Nonlinear-Diffusion model (GPU) \n'); % iter_diff = 800; % number of diffusion iterations -% lambda_regDiff = 0.06; % regularisation for the diffusivity -% sigmaPar = 0.04; % edge-preserving parameter +% lambda_regDiff = 0.025; % regularisation for the diffusivity +% sigmaPar = 0.015; % edge-preserving parameter % tau_param = 0.025; % time-marching constant % tic; u_diff_g = NonlDiff_GPU(single(u0), lambda_regDiff, sigmaPar, iter_diff, tau_param, 'Huber'); toc; % figure; imshow(u_diff_g, [0 1]); title('Diffusion denoised image (GPU)'); |