% SHOW_DENOISING Image denosing of USPS hand-written numerals.%% Description:%  The input noisy images are denoised using the %  kernel PCA model. The denosing based on linear PCA%  is also computed for comparision. Imgase of%   - Ground truth numerlas%   - Noisy numerals%   - Numerals denoised by kernel PCA%   - Numerals denoised by linear PCA%  are displayed.%% See also%  KPCAREC, PCAREC.%% About: Statistical Pattern Recognition Toolbox% (C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac% <a href="http://www.cvut.cz">Czech Technical University Prague</a>% <a href="http://www.feld.cvut.cz">Faculty of Electrical Engineering</a>% <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a>% Modification:% 07-jun-2004, VF% 05-may-2004, VF% 22-apr-2004, VFhelp show_denoising;% setting %-------------------------------------------------------kpca_filename = 'USPSModelGreedyKPCA.mat'; % kpca modellpca_filename = 'USPSModelLinPCA.mat';     % linear PCA model% USPS databes with noisy images (see help make_noisy_usps).input_data_file = '/home.dokt/xfrancv/data/usps/usps_noisy';% loading%----------------------------------------load(kpca_filename,'kpca_model');load(lpca_filename,'lpca_model');load(input_data_file,'tst');% get indices of examples to be denoised% ---------------------------------------inx = [];for i=1:10,  tmp = find(tst.y == i);  inx = [inx, tmp(1) ];end% get noisy and ground truth numerals%----------------------------------------noisy_X = tst.X(:,inx);  gnd_X = tst.gnd_X(:,inx);% Kernel PCA and linear PCA denoising%----------------------------------------kpca_X = kpcarec( noisy_X, kpca_model);lpca_X = pcarec( noisy_X, lpca_model);% display results%----------------------------------------h=figure; set(h,'name','Denoised by greedy KPCA');showim( kpca_X);h=figure; set(h,'name','Denoised by linear PCA');showim( lpca_X);h=figure; set(h,'name','Ground truth');showim( gnd_X);h=figure; set(h,'name','Noisy');showim( noisy_X);%EOF