comparison examples/Image Denoising/SMALL_ImgDenoise_DL_test_TwoStep_KSVD_MOD_OLS_Mailhe.m @ 161:f42aa8bcb82f ivand_dev

debug and clean the SMALLbox Problems code

 %   (backward compatiblity with SPARCO: solver structure communicate
 %   only with Problem structure, ie no direct communication between DL and
 %   solver structures)
 
 SMALL.Problem.A = SMALL.DL(1).D;
-SMALL.Problem.reconstruct = @(x) ImgDenoise_reconstruct(x, SMALL.Problem);
+SMALL.Problem.reconstruct = @(x) ImageDenoise_reconstruct(x, SMALL.Problem);
 
 %   Denoising the image - find the sparse solution in the learned
 %   dictionary for all patches in the image and the end it uses
 %   reconstruction function to reconstruct the patches and put them into a
 %   denoised image

 %   (backward compatiblity with SPARCO: solver structure communicate
 %   only with Problem structure, ie no direct communication between DL and
 %   solver structures)
 
 SMALL.Problem.A = SMALL.DL(2).D;
-SMALL.Problem.reconstruct = @(x) ImgDenoise_reconstruct(x, SMALL.Problem);
+SMALL.Problem.reconstruct = @(x) ImageDenoise_reconstruct(x, SMALL.Problem);
 
 %   Denoising the image - find the sparse solution in the learned
 %   dictionary for all patches in the image and the end it uses
 %   reconstruction function to reconstruct the patches and put them into a
 %   denoised image

 %   (backward compatiblity with SPARCO: solver structure communicate
 %   only with Problem structure, ie no direct communication between DL and
 %   solver structures)
 
 SMALL.Problem.A = SMALL.DL(3).D;
-SMALL.Problem.reconstruct = @(x) ImgDenoise_reconstruct(x, SMALL.Problem);
+SMALL.Problem.reconstruct = @(x) ImageDenoise_reconstruct(x, SMALL.Problem);
 
 %   Denoising the image - find the sparse solution in the learned
 %   dictionary for all patches in the image and the end it uses
 %   reconstruction function to reconstruct the patches and put them into a
 %   denoised image

 %   (backward compatiblity with SPARCO: solver structure communicate
 %   only with Problem structure, ie no direct communication between DL and
 %   solver structures)
 
 SMALL.Problem.A = SMALL.DL(4).D;
-SMALL.Problem.reconstruct = @(x) ImgDenoise_reconstruct(x, SMALL.Problem);
+SMALL.Problem.reconstruct = @(x) ImageDenoise_reconstruct(x, SMALL.Problem);
 
 %   Denoising the image - find the sparse solution in the learned
 %   dictionary for all patches in the image and the end it uses
 %   reconstruction function to reconstruct the patches and put them into a
 %   denoised image