changeset 118:ceb81fd882aa sup_158_IMG_Processing_toolbox_

removed old versions of ssim and vmrse

--- a/util/ssim_index.m	Tue May 24 16:15:05 2011 +0100
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,194 +0,0 @@
-function [mssim, ssim_map] = ssim_index(img1, img2, K, window, L)
-
-%========================================================================
-%SSIM Index, Version 1.0
-%Copyright(c) 2003 Zhou Wang
-%All Rights Reserved.
-%
-%The author is with Howard Hughes Medical Institute, and Laboratory
-%for Computational Vision at Center for Neural Science and Courant
-%Institute of Mathematical Sciences, New York University.
-%
-%----------------------------------------------------------------------
-%Permission to use, copy, or modify this software and its documentation
-%for educational and research purposes only and without fee is hereby
-%granted, provided that this copyright notice and the original authors'
-%names appear on all copies and supporting documentation. This program
-%shall not be used, rewritten, or adapted as the basis of a commercial
-%software or hardware product without first obtaining permission of the
-%authors. The authors make no representations about the suitability of
-%this software for any purpose. It is provided "as is" without express
-%or implied warranty.
-%----------------------------------------------------------------------
-%
-%This is an implementation of the algorithm for calculating the
-%Structural SIMilarity (SSIM) index between two images. Please refer
-%to the following paper:
-%
-%Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image
-%quality assessment: From error measurement to structural similarity"
-%IEEE Transactios on Image Processing, vol. 13, no. 1, Jan. 2004.
-%
-%Kindly report any suggestions or corrections to [e-mail]
-%
-%----------------------------------------------------------------------
-%
-%Input : (1) img1: the first image being compared
-%        (2) img2: the second image being compared
-%        (3) K: constants in the SSIM index formula (see the above
-%            reference). defualt value: K = [0.01 0.03]
-%        (4) window: local window for statistics (see the above
-%            reference). default widnow is Gaussian given by
-%            window = fspecial('gaussian', 11, 1.5);
-%        (5) L: dynamic range of the images. default: L = 255
-%
-%Output: (1) mssim: the mean SSIM index value between 2 images.
-%            If one of the images being compared is regarded as 
-%            perfect quality, then mssim can be considered as the
-%            quality measure of the other image.
-%            If img1 = img2, then mssim = 1.
-%        (2) ssim_map: the SSIM index map of the test image. The map
-%            has a smaller size than the input images. The actual size:
-%            size(img1) - size(window) + 1.
-%
-%Default Usage:
-%   Given 2 test images img1 and img2, whose dynamic range is 0-255
-%
-%   [mssim ssim_map] = ssim_index(img1, img2);
-%
-%Advanced Usage:
-%   User defined parameters. For example
-%
-%   K = [0.05 0.05];
-%   window = ones(8);
-%   L = 100;
-%   [mssim ssim_map] = ssim_index(img1, img2, K, window, L);
-%
-%See the results:
-%
-%   mssim                        %Gives the mssim value
-%   imshow(max(0, ssim_map).^4)  %Shows the SSIM index map
-%
-%========================================================================
-
-
-if (nargin < 2 || nargin > 5)
-   ssim_index = -Inf;
-   ssim_map = -Inf;
-   return;
-end
-
-if (size(img1) ~= size(img2))
-   ssim_index = -Inf;
-   ssim_map = -Inf;
-   return;
-end
-
-[M N] = size(img1);
-
-if (nargin == 2)
-   if ((M < 11) || (N < 11))
-	   ssim_index = -Inf;
-	   ssim_map = -Inf;
-      return
-   end
-   window = fspecial('gaussian', 11, 1.5);	%
-   K(1) = 0.01;								      % default settings
-   K(2) = 0.03;								      %
-   L = 255;                                  %
-end
-
-if (nargin == 3)
-   if ((M < 11) || (N < 11))
-	   ssim_index = -Inf;
-	   ssim_map = -Inf;
-      return
-   end
-   window = fspecial('gaussian', 11, 1.5);
-   L = 255;
-   if (length(K) == 2)
-      if (K(1) < 0 || K(2) < 0)
-		   ssim_index = -Inf;
-   		ssim_map = -Inf;
-	   	return;
-      end
-   else
-	   ssim_index = -Inf;
-   	ssim_map = -Inf;
-	   return;
-   end
-end
-
-if (nargin == 4)
-   [H W] = size(window);
-   if ((H*W) < 4 || (H > M) || (W > N))
-	   ssim_index = -Inf;
-	   ssim_map = -Inf;
-      return
-   end
-   L = 255;
-   if (length(K) == 2)
-      if (K(1) < 0 || K(2) < 0)
-		   ssim_index = -Inf;
-   		ssim_map = -Inf;
-	   	return;
-      end
-   else
-	   ssim_index = -Inf;
-   	ssim_map = -Inf;
-	   return;
-   end
-end
-
-if (nargin == 5)
-   [H W] = size(window);
-   if ((H*W) < 4 || (H > M) || (W > N))
-	   ssim_index = -Inf;
-	   ssim_map = -Inf;
-      return
-   end
-   if (length(K) == 2)
-      if (K(1) < 0 || K(2) < 0)
-		   ssim_index = -Inf;
-   		ssim_map = -Inf;
-	   	return;
-      end
-   else
-	   ssim_index = -Inf;
-   	ssim_map = -Inf;
-	   return;
-   end
-end
-
-C1 = (K(1)*L)^2;
-C2 = (K(2)*L)^2;
-window = window/sum(sum(window));
-img1 = double(img1);
-img2 = double(img2);
-
-mu1   = filter2(window, img1, 'valid');
-mu2   = filter2(window, img2, 'valid');
-mu1_sq = mu1.*mu1;
-mu2_sq = mu2.*mu2;
-mu1_mu2 = mu1.*mu2;
-sigma1_sq = filter2(window, img1.*img1, 'valid') - mu1_sq;
-sigma2_sq = filter2(window, img2.*img2, 'valid') - mu2_sq;
-sigma12 = filter2(window, img1.*img2, 'valid') - mu1_mu2;
-
-if (C1 > 0 & C2 > 0)
-   ssim_map = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))./((mu1_sq + mu2_sq + C1).*(sigma1_sq + sigma2_sq + C2));
-else
-   numerator1 = 2*mu1_mu2 + C1;
-   numerator2 = 2*sigma12 + C2;
-	denominator1 = mu1_sq + mu2_sq + C1;
-   denominator2 = sigma1_sq + sigma2_sq + C2;
-   ssim_map = ones(size(mu1));
-   index = (denominator1.*denominator2 > 0);
-   ssim_map(index) = (numerator1(index).*numerator2(index))./(denominator1(index).*denominator2(index));
-   index = (denominator1 ~= 0) & (denominator2 == 0);
-   ssim_map(index) = numerator1(index)./denominator1(index);
-end
-
-mssim = mean2(ssim_map);
-
-return
\ No newline at end of file

--- a/util/vmrse_type2.m	Tue May 24 16:15:05 2011 +0100
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,43 +0,0 @@
-function [RMSErn, RMSEcd, rn_im, cd_im] = vmrse_type2(orig, corr, recon)
-
-%%%   Implementation of VectorRMSE type2
-%
-%   Centre for Digital Music, Queen Mary, University of London.
-%   This file copyright 2011 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.
-% 
-%   Input:
-%       - Original image
-%       - Corrupted image
-%       - Reconstructed Image
-%
-%   Output:
-%       - RMSErn - RMSE from residual noise (noise not completely removed)
-%       - RMSEcd - RMSE from collateral distortion - excessive filtering
-%       - rn_im  - image of residual noise
-%       - cd_im  - image of collateral distortion
-%
-%   F. Russo, "New Method for Performance Evaluation of Grayscale Image
-%   Denoising filters", IEEE Signal Processing Letters, vol. 17, no. 5,
-%   pp.417-420, May 2010
-%%
-
-    recon_int = round(recon);
-    
-    RN1 = ((orig<recon_int)&(recon_int<=corr));
-    RN2 = ((orig>recon_int)&(recon_int>=corr));
-    CD1 = ((orig<recon_int)&(recon_int>corr));
-    CD2 = ((orig>recon_int)&(recon_int<corr));
-    
-    RMSErn = sqrt(sum(sum((RN1+RN2).*(orig-recon).^2)))/512;
-    RMSEcd = sqrt(sum(sum((CD1+CD2).*(orig-recon).^2)))/512;
-    rn_im=RN1+RN2;
-    cd_im=CD1+CD2;
-    
-end
-