diff options
Diffstat (limited to 'demos/demoMatlab_3Ddenoise.m')
| -rw-r--r-- | demos/demoMatlab_3Ddenoise.m | 16 |
1 files changed, 12 insertions, 4 deletions
diff --git a/demos/demoMatlab_3Ddenoise.m b/demos/demoMatlab_3Ddenoise.m index cdd3117..cf2c88a 100644 --- a/demos/demoMatlab_3Ddenoise.m +++ b/demos/demoMatlab_3Ddenoise.m @@ -8,7 +8,7 @@ addpath(Path2); addpath(Path3); N = 512; -slices = 7; +slices = 15; vol3D = zeros(N,N,slices, 'single'); Ideal3D = zeros(N,N,slices, 'single'); Im = double(imread('lena_gray_512.tif'))/255; % loading image @@ -17,9 +17,7 @@ vol3D(:,:,i) = Im + .05*randn(size(Im)); Ideal3D(:,:,i) = Im; end vol3D(vol3D < 0) = 0; -figure; imshow(vol3D(:,:,15), [0 1]); title('Noisy image'); - - +figure; imshow(vol3D(:,:,7), [0 1]); title('Noisy image'); lambda_reg = 0.03; % regularsation parameter for all methods %% fprintf('Denoise a volume using the ROF-TV model (CPU) \n'); @@ -143,6 +141,16 @@ rmseTGV = RMSE(Ideal3D(:),u_tgv(:)); fprintf('%s %f \n', 'RMSE error for TGV is:', rmseTGV); figure; imshow(u_tgv(:,:,3), [0 1]); title('TGV denoised volume (CPU)'); %% +% fprintf('Denoise using the TGV model (GPU) \n'); +% lambda_TGV = 0.03; % regularisation parameter +% alpha1 = 1.0; % parameter to control the first-order term +% alpha0 = 2.0; % parameter to control the second-order term +% iter_TGV = 500; % number of Primal-Dual iterations for TGV +% tic; u_tgv_gpu = TGV_GPU(single(vol3D), lambda_TGV, alpha1, alpha0, iter_TGV); toc; +% rmseTGV = RMSE(Ideal3D(:),u_tgv_gpu(:)); +% fprintf('%s %f \n', 'RMSE error for TGV is:', rmseTGV); +% figure; imshow(u_tgv_gpu(:,:,3), [0 1]); title('TGV denoised volume (GPU)'); +%% %>>>>>>>>>>>>>> MULTI-CHANNEL priors <<<<<<<<<<<<<<< % fprintf('Denoise a volume using the FGP-dTV model (CPU) \n'); |