changeset 125:002ec1b2ceff sup_158_IMG_Processing_toolbox_

cleaning up. All IMP toolbox dependencies removed

--- a/Problems/Pierre_Problem.m	Wed May 25 15:20:04 2011 +0100
+++ b/Problems/Pierre_Problem.m	Wed May 25 15:29:20 2011 +0100
@@ -1,14 +1,5 @@
 function data=Pierre_Problem(src, trg, blocksize, dictsize);
-%%% Generate Pierre Problem
-%
-%   Centre for Digital Music, Queen Mary, University of London.
-%   This file copyright 2010 Ivan Damnjanovic.
-%
-%   This program is free software; you can redistribute it and/or
-%   modify it under the terms of the GNU General Public License as
-%   published by the Free Software Foundation; either version 2 of the
-%   License, or (at your option) any later version.  See the file
-%   COPYING included with this distribution for more information.
+%% Generate Pierre Problem
 %
 %   Pierre_Problem is a part of the SMALLbox and generates the problem
 %   suggested by Professor Pierre Vandergheynst on the SMALL meeting in 
@@ -38,6 +29,15 @@
 %   -   sparse - if 1 SMALL_solve will keep solution matrix in sparse form,
 %                due to memory constrains.
 
+%
+%   Centre for Digital Music, Queen Mary, University of London.
+%   This file copyright 2010 Ivan Damnjanovic.
+%
+%   This program is free software; you can redistribute it and/or
+%   modify it under the terms of the GNU General Public License as
+%   published by the Free Software Foundation; either version 2 of the
+%   License, or (at your option) any later version.  See the file
+%   COPYING included with this distribution for more information.
 %% prompt user for images %%
 
 %   ask for source file name

--- a/Problems/generateImageDenoiseProblem.m	Wed May 25 15:20:04 2011 +0100
+++ b/Problems/generateImageDenoiseProblem.m	Wed May 25 15:29:20 2011 +0100
@@ -1,14 +1,5 @@
 function data=generateImageDenoiseProblem(im, trainnum, blocksize, dictsize, sigma, gain, maxval, initdict);
-%%% Generate Image Denoising Problem
-%
-%   Centre for Digital Music, Queen Mary, University of London.
-%   This file copyright 2010 Ivan Damnjanovic.
-%
-%   This program is free software; you can redistribute it and/or
-%   modify it under the terms of the GNU General Public License as
-%   published by the Free Software Foundation; either version 2 of the
-%   License, or (at your option) any later version.  See the file
-%   COPYING included with this distribution for more information.
+%% Generate Image Denoising Problem
 %   
 %   generateImageDenoiseProblem is a part of the SMALLbox and generates
 %   a problem that can be used for comparison of Dictionary Learning/Sparse
@@ -39,6 +30,16 @@
 %   -   maxval - maximum value (default - 255)
 %   -   initdict - initial dictionary (default - 4x overcomlete dct)
 %   -   signalDim - signal dimension (default - 2)
+
+%
+%   Centre for Digital Music, Queen Mary, University of London.
+%   This file copyright 2010 Ivan Damnjanovic.
+%
+%   This program is free software; you can redistribute it and/or
+%   modify it under the terms of the GNU General Public License as
+%   published by the Free Software Foundation; either version 2 of the
+%   License, or (at your option) any later version.  See the file
+%   COPYING included with this distribution for more information.
 %
 %   Based on KSVD denoise demo by Ron Rubinstein
 %   See also KSVDDENOISEDEMO and KSVDDEMO.

--- a/examples/SMALL_solver_test.m	Wed May 25 15:20:04 2011 +0100
+++ b/examples/SMALL_solver_test.m	Wed May 25 15:29:20 2011 +0100
@@ -1,6 +1,5 @@
 function SMALL_solver_test
-%   Example test of solvers from different toolboxes on Sparco compressed
-%   sensing problems
+%%   Example test of solvers from different toolboxes on Sparco problem 6
 %
 %   The main purpose of this example is to show how to use SMALL structure
 %   to solve SPARCO compressed sensing problems (1-11) and compare results

--- a/util/Pierre_reconstruct.m	Wed May 25 15:20:04 2011 +0100
+++ b/util/Pierre_reconstruct.m	Wed May 25 15:29:20 2011 +0100
@@ -1,5 +1,11 @@
 function reconstructed=Pierre_reconstruct(y, Problem)
-%%%  Pierre Villars Example - reconstruction function
+%%  Pierre Villars Example - reconstruction function
+%
+%   using sparse representation y in dictionary Problem.A reconstruct the
+%   patches from the target image
+%   This example is based on the experiment suggested by Professor Pierre
+%   Vandergheynst on the SMALL meeting in Villars.
+
 %
 %   Centre for Digital Music, Queen Mary, University of London.
 %   This file copyright 2009 Ivan Damnjanovic.
@@ -10,12 +16,7 @@
 %   License, or (at your option) any later version.  See the file
 %   COPYING included with this distribution for more information.
 %   
-%   This example is based on the experiment suggested by Professor Pierre
-%   Vandergheynst on the SMALL meeting in Villars.
-
-%   using sparse representation y in dictionary Problem.A reconstruct the
-%   patches from the target image
-
+%%
 imout=Problem.A*y;
 
 %   combine the patches into reconstructed image

--- a/util/SMALL_ImgDeNoiseResult.m	Wed May 25 15:20:04 2011 +0100
+++ b/util/SMALL_ImgDeNoiseResult.m	Wed May 25 15:29:20 2011 +0100
@@ -1,5 +1,11 @@
-function SMALL_ImgDeNoiseResult(SMALL)
+function SMALL_ImgDeNoiseResult(SMALL)   
+%%  Represents the results of Dictionary Learning for Image denoising
 %
+%   Function gets as input SMALL structure and plots  Image Denoise
+%   results: Original Image, Noisy Image and for learned dictionaries and 
+%   denoised images 
+%
+
 %   Centre for Digital Music, Queen Mary, University of London.
 %   This file copyright 2010 Ivan Damnjanovic.
 %
@@ -8,10 +14,7 @@
 %   published by the Free Software Foundation; either version 2 of the
 %   License, or (at your option) any later version.  See the file
 %   COPYING included with this distribution for more information.
-%   
-%   Function gets as input SMALL structure and plots  Image Denoise
-%   results: Original Image, Noisy Image and for learned dictionaries and 
-%   denoised images 
+%%
 
 
 figure('Name', sprintf('Image %s (training set size- %d, sigma - %d)',SMALL.Problem.name, SMALL.Problem.n, SMALL.Problem.sigma));