new inpainters

3 files changed, 45 insertions, 8 deletions

diff --git a/Wrappers/Matlab/demos/demoMatlab_3Ddenoise.m b/Wrappers/Matlab/demos/demoMatlab_3Ddenoise.m
index 5a54d18..c087433 100644
--- a/Wrappers/Matlab/demos/demoMatlab_3Ddenoise.m
+++ b/Wrappers/Matlab/demos/demoMatlab_3Ddenoise.m
@@ -1,8 +1,9 @@
 % Volume (3D) denoising demo using CCPi-RGL
-clear
-close all
-addpath('../mex_compile/installed');
-addpath('../../../data/');
+clear; close all
+Path1 = sprintf(['..' filesep 'mex_compile' filesep 'installed'], 1i);
+Path2 = sprintf(['..' filesep '..' filesep '..' filesep 'data' filesep], 1i);
+addpath(Path1);
+addpath(Path2);
 
 N = 512; 
 slices = 30;
diff --git a/Wrappers/Matlab/demos/demoMatlab_denoise.m b/Wrappers/Matlab/demos/demoMatlab_denoise.m
index 151a604..d93f477 100644
--- a/Wrappers/Matlab/demos/demoMatlab_denoise.m
+++ b/Wrappers/Matlab/demos/demoMatlab_denoise.m
@@ -1,8 +1,9 @@
 % Image (2D) denoising demo using CCPi-RGL
-clear
-close all
-addpath('../mex_compile/installed');
-addpath('../../../data/');
+clear; close all
+Path1 = sprintf(['..' filesep 'mex_compile' filesep 'installed'], 1i);
+Path2 = sprintf(['..' filesep '..' filesep '..' filesep 'data' filesep], 1i);
+addpath(Path1);
+addpath(Path2);
 
 Im = double(imread('lena_gray_512.tif'))/255;  % loading image
 u0 = Im + .05*randn(size(Im)); u0(u0 < 0) = 0;
diff --git a/Wrappers/Matlab/demos/demoMatlab_inpaint.m b/Wrappers/Matlab/demos/demoMatlab_inpaint.m
new file mode 100644
index 0000000..66f9c15
--- /dev/null
+++ b/Wrappers/Matlab/demos/demoMatlab_inpaint.m
@@ -0,0 +1,35 @@
+% Image (2D) inpainting demo using CCPi-RGL
+clear; close all
+Path1 = sprintf(['..' filesep 'mex_compile' filesep 'installed'], 1i);
+Path2 = sprintf(['..' filesep '..' filesep '..' filesep 'data' filesep], 1i);
+addpath(Path1);
+addpath(Path2);
+
+load('SinoInpaint.mat');
+Sinogram = Sinogram./max(Sinogram(:));
+Sino_mask = Sinogram.*(1-single(Mask));
+figure; 
+subplot(1,2,1); imshow(Sino_mask, [0 1]); title('Missing data sinogram');
+subplot(1,2,2); imshow(Mask, [0 1]); title('Mask');
+%%
+fprintf('Inpaint using Linear-Diffusion model (CPU) \n');
+iter_diff = 5000; % number of diffusion iterations
+lambda_regDiff = 6000; % regularisation for the diffusivity 
+sigmaPar = 0.0; % edge-preserving parameter
+tau_param = 0.000075; % time-marching constant 
+tic; u_diff = NonlDiff_Inp(single(Sino_mask), Mask, lambda_regDiff, sigmaPar, iter_diff, tau_param); toc; 
+figure; imshow(u_diff, [0 1]); title('Linear-Diffusion inpainted sinogram (CPU)');
+%%
+fprintf('Inpaint using Nonlinear-Diffusion model (CPU) \n');
+iter_diff = 1500; % number of diffusion iterations
+lambda_regDiff = 80; % regularisation for the diffusivity 
+sigmaPar = 0.00009; % edge-preserving parameter
+tau_param = 0.000008; % time-marching constant 
+tic; u_diff = NonlDiff_Inp(single(Sino_mask), Mask, lambda_regDiff, sigmaPar, iter_diff, tau_param, 'Huber'); toc; 
+figure; imshow(u_diff, [0 1]); title('Non-Linear Diffusion inpainted sinogram (CPU)');
+%%
+fprintf('Inpaint using Nonlocal Vertical Marching model (CPU) \n');
+Increment = 1; % linear increment for the searching window
+tic; [u_nom,maskupd] = NonlocalMarching_Inpaint(single(Sino_mask), Mask, Increment); toc;
+figure; imshow(u_nom, [0 1]); title('NVM inpainted sinogram (CPU)');
+%%
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