diff options
Diffstat (limited to 'demos/demoMatlab_denoise.m')
| -rw-r--r-- | demos/demoMatlab_denoise.m | 12 |
1 files changed, 7 insertions, 5 deletions
diff --git a/demos/demoMatlab_denoise.m b/demos/demoMatlab_denoise.m index 5e92ee1..fa81f6d 100644 --- a/demos/demoMatlab_denoise.m +++ b/demos/demoMatlab_denoise.m @@ -2,9 +2,11 @@ clear; close all fsep = '/'; -Path1 = sprintf(['..' fsep 'src' fsep 'Matlab' fsep 'mex_compile' fsep 'installed'], 1i); -Path2 = sprintf([ data' fsep], 1i); -Path3 = sprintf(['..' filesep 'src' filesep 'Matlab' filesep 'supp'], 1i); +%Path1 = sprintf(['..' fsep 'src' fsep 'Matlab' fsep 'mex_compile' fsep 'installed'], 1i); +Path1 = ('/home/kjy41806/Documents/SOFT/CCPi-Regularisation-Toolkit/src/Matlab/mex_compile/installed'); +Path2 = sprintf(['data' fsep], 1i); +%Path3 = sprintf(['..' filesep 'src' filesep 'Matlab' filesep 'supp'], 1i); +Path3 = '/home/kjy41806/Documents/SOFT/CCPi-Regularisation-Toolkit/src/Matlab/supp'; addpath(Path1); addpath(Path2); addpath(Path3); @@ -34,8 +36,8 @@ figure; imshow(u_rof, [0 1]); title('ROF-TV denoised image (CPU)'); %% fprintf('Denoise using the FGP-TV model (CPU) \n'); lambda_reg = 0.033; -iter_fgp = 300; % number of FGP iterations -epsil_tol = 1.0e-09; % tolerance +iter_fgp = 200; % number of FGP iterations +epsil_tol = 1.0e-05; % tolerance tic; u_fgp = FGP_TV(single(u0), lambda_reg, iter_fgp, epsil_tol); toc; energyfunc_val_fgp = TV_energy(single(u_fgp),single(u0),lambda_reg, 1); % get energy function value rmseFGP = (RMSE(u_fgp(:),Im(:))); |