diff examples/Image Denoising/SMALL_ImgDenoise_UNLocBox.m @ 244:5c8bcdadb380 unlocbox

added UNLocBox interface, example and a 128x128 Lena

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/examples/Image Denoising/SMALL_ImgDenoise_UNLocBox.m	Tue Sep 04 11:00:36 2012 +0100
@@ -0,0 +1,85 @@
+%% Demostration of the use of the UNLocBox solver to solve an image denoising problem of the SMALLBox form
+%
+% argmin_x ||x||_1 such that ||Ax-b||_2 < sima_t
+%
+%   The dictionary A is first learn using SMALLbox
+%
+% Queen Mary University
+% 29 August 2012
+% Nathanael Perraudin
+% [e-mail]
+
+
+% % Initialisation
+% clear all;
+% close all;
+% clc;
+
+
+%% Load an image and create the problem
+
+% Defining Image Denoising Problem as Dictionary Learning
+% Problem. As an input we set the number of training patches.
+
+SMALL.Problem = generateImageDenoiseProblem('', 40000);
+
+
+%%
+%   Use KSVD Dictionary Learning Algorithm to Learn overcomplete dictionary
+
+%   Initialising Dictionary structure
+%   Setting Dictionary structure fields (toolbox, name, param, D and time)
+%   to zero values
+
+SMALL.DL=SMALL_init_DL();
+
+% Defining the parameters needed for dictionary learning
+
+SMALL.DL.toolbox = 'KSVD';
+SMALL.DL.name = 'ksvd';
+
+%   Defining the parameters for KSVD
+%   In this example we are learning 256 atoms in 20 iterations, so that
+%   every patch in the training set can be represented with target error in
+%   L2-norm (EData)
+%   Type help ksvd in MATLAB prompt for more options.
+
+Edata=sqrt(prod(SMALL.Problem.blocksize)) * SMALL.Problem.sigma * SMALL.Problem.gain;
+maxatoms = floor(prod(SMALL.Problem.blocksize)/2);
+
+SMALL.DL.param=struct(...
+    'Edata', Edata,...
+    'initdict', SMALL.Problem.initdict,...
+    'dictsize', SMALL.Problem.p,...
+    'iternum', 20,...
+    'memusage', 'high');
+
+%   Learn the dictionary
+
+SMALL.DL = SMALL_learn(SMALL.Problem, SMALL.DL(1));
+
+%   Set SMALL.Problem.A dictionary
+%   (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.D;
+SMALL.Problem.reconstruct = @(x) ImageDenoise_reconstruct(x, SMALL.Problem);
+
+%% Solving the problem with UNLocBox
+% This might not be the better way to solve the problem...
+
+
+% Set the different parameter
+
+SMALL.solver=SMALL_init_solver; % Initialisation
+SMALL.solver.toolbox='UNLocBox';     % select the UNLocBox solver
+SMALL.solver.name='Douglas_Rachford'; % 'Forward_Backard' 'ADMM' Warning forward backward still need some review...
+SMALL.solver.param.sigma=1.15*sqrt(SMALL.Problem.m*SMALL.Problem.n)*SMALL.Problem.sigma; % set the radius of the ball
+SMALL.solver.param.max_iter=100;
+
+
+SMALL.solver=SMALL_solve(SMALL.Problem, SMALL.solver);
+
+
+SMALL_ImgDeNoiseResult(SMALL);
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