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| author | Daniil Kazantsev <dkazanc@hotmail.com> | 2019-11-28 23:01:03 +0000 |
|---|---|---|
| committer | Daniil Kazantsev <dkazanc@hotmail.com> | 2019-11-28 23:01:03 +0000 |
| commit | c65291e6b987283e4767a8ad2bd2d2433ca3782e (patch) | |
| tree | c3b660c9b2151f2ff1a12352daf73dfc90d1c3a3 /demos/Matlab_demos | |
| parent | cdef6a981f1772ed04fe44bbe2b8251983a4ba7a (diff) | |
| download | regularization-c65291e6b987283e4767a8ad2bd2d2433ca3782e.tar.gz regularization-c65291e6b987283e4767a8ad2bd2d2433ca3782e.tar.bz2 regularization-c65291e6b987283e4767a8ad2bd2d2433ca3782e.tar.xz regularization-c65291e6b987283e4767a8ad2bd2d2433ca3782e.zip | |
all work completed on gpu version of pdtv
Diffstat (limited to 'demos/Matlab_demos')
| -rw-r--r-- | demos/Matlab_demos/demoMatlab_3Ddenoise.m | 19 | ||||
| -rw-r--r-- | demos/Matlab_demos/demoMatlab_denoise.m | 16 |
2 files changed, 35 insertions, 0 deletions
diff --git a/demos/Matlab_demos/demoMatlab_3Ddenoise.m b/demos/Matlab_demos/demoMatlab_3Ddenoise.m index f018327..b7f92cb 100644 --- a/demos/Matlab_demos/demoMatlab_3Ddenoise.m +++ b/demos/Matlab_demos/demoMatlab_3Ddenoise.m @@ -62,6 +62,25 @@ fprintf('Denoise a volume using the FGP-TV model (GPU) \n'); % fprintf('%s %f \n', 'RMSE error for FGP-TV is:', rmse_fgpG); % figure; imshow(u_fgpG(:,:,7), [0 1]); title('FGP-TV denoised volume (GPU)'); %% +fprintf('Denoise a volume using the PD-TV model (CPU) \n'); +lambda_reg = 0.03; % regularsation parameter for all methods +iter_pd = 300; % number of FGP iterations +epsil_tol = 0.0; % tolerance +tic; [u_pd,infovec] = PD_TV(single(vol3D), lambda_reg, iter_pd, epsil_tol); toc; +energyfunc_val_fgp = TV_energy(single(u_pd),single(vol3D),lambda_reg, 1); % get energy function value +rmse_pd = (RMSE(Ideal3D(:),u_pd(:))); +fprintf('%s %f \n', 'RMSE error for PD-TV is:', rmse_pd); +figure; imshow(u_pd(:,:,7), [0 1]); title('PD-TV denoised volume (CPU)'); +%% +% fprintf('Denoise a volume using the PD-TV model (GPU) \n'); +% lambda_reg = 0.03; % regularsation parameter for all methods +% iter_pd = 300; % number of FGP iterations +% epsil_tol = 0.0; % tolerance +% tic; u_pdG = PD_TV_GPU(single(vol3D), lambda_reg, iter_pd, epsil_tol); toc; +% rmse_pdG = (RMSE(Ideal3D(:),u_pdG(:))); +% fprintf('%s %f \n', 'RMSE error for PD-TV is:', rmse_pdG); +% figure; imshow(u_pdG(:,:,7), [0 1]); title('PD-TV denoised volume (GPU)'); +%% fprintf('Denoise a volume using the SB-TV model (CPU) \n'); iter_sb = 150; % number of SB iterations epsil_tol = 0.0; % tolerance diff --git a/demos/Matlab_demos/demoMatlab_denoise.m b/demos/Matlab_demos/demoMatlab_denoise.m index b50eaf5..3d93cb6 100644 --- a/demos/Matlab_demos/demoMatlab_denoise.m +++ b/demos/Matlab_demos/demoMatlab_denoise.m @@ -46,6 +46,22 @@ figure; imshow(u_fgp, [0 1]); title('FGP-TV denoised image (CPU)'); % tic; u_fgpG = FGP_TV_GPU(single(u0), lambda_reg, iter_fgp, epsil_tol); toc; % figure; imshow(u_fgpG, [0 1]); title('FGP-TV denoised image (GPU)'); %% +fprintf('Denoise using the PD-TV model (CPU) \n'); +lambda_reg = 0.03; +iter_pd = 500; % number of FGP iterations +epsil_tol = 0.0; % tolerance +tic; [u_pd,infovec] = PD_TV(single(u0), lambda_reg, iter_pd, epsil_tol); toc; +energyfunc_val_pd = TV_energy(single(u_pd),single(u0),lambda_reg, 1); % get energy function value +rmsePD = (RMSE(u_pd(:),Im(:))); +fprintf('%s %f \n', 'RMSE error for PD-TV is:', rmsePD); +[ssimval] = ssim(u_pd*255,single(Im)*255); +fprintf('%s %f \n', 'MSSIM error for PD-TV is:', ssimval); +figure; imshow(u_pd, [0 1]); title('PD-TV denoised image (CPU)'); +%% +% fprintf('Denoise using the PD-TV model (GPU) \n'); +% tic; u_pdG = PD_TV_GPU(single(u0), lambda_reg, iter_pd, epsil_tol); toc; +% figure; imshow(u_pdG, [0 1]); title('PD-TV denoised image (GPU)'); +%% fprintf('Denoise using the SB-TV model (CPU) \n'); lambda_reg = 0.03; iter_sb = 200; % number of SB iterations |