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1 function [mssim, ssim_map] = SMALL_ssim_index(img1, img2, K, window, L)
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2
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3 %========================================================================
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4 %SSIM Index, Version 1.0
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5 %Copyright(c) 2003 Zhou Wang
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6 %All Rights Reserved.
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7 %
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8 %The author is with Howard Hughes Medical Institute, and Laboratory
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9 %for Computational Vision at Center for Neural Science and Courant
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10 %Institute of Mathematical Sciences, New York University.
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11 %
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12 %----------------------------------------------------------------------
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13 %Permission to use, copy, or modify this software and its documentation
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14 %for educational and research purposes only and without fee is hereby
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15 %granted, provided that this copyright notice and the original authors'
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16 %names appear on all copies and supporting documentation. This program
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17 %shall not be used, rewritten, or adapted as the basis of a commercial
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18 %software or hardware product without first obtaining permission of the
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19 %authors. The authors make no representations about the suitability of
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20 %this software for any purpose. It is provided "as is" without express
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21 %or implied warranty.
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22 %----------------------------------------------------------------------
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23 %
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24 %This is an implementation of the algorithm for calculating the
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25 %Structural SIMilarity (SSIM) index between two images. Please refer
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26 %to the following paper:
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27 %
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28 %Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image
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29 %quality assessment: From error measurement to structural similarity"
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30 %IEEE Transactios on Image Processing, vol. 13, no. 1, Jan. 2004.
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31 %
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32 %Kindly report any suggestions or corrections to zhouwang@ieee.org
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33 %
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34 %----------------------------------------------------------------------
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35 %
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36 %Input : (1) img1: the first image being compared
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37 % (2) img2: the second image being compared
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38 % (3) K: constants in the SSIM index formula (see the above
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39 % reference). defualt value: K = [0.01 0.03]
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40 % (4) window: local window for statistics (see the above
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41 % reference). default widnow is Gaussian given by
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42 % window = fspecial('gaussian', 11, 1.5);
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43 % (5) L: dynamic range of the images. default: L = 255
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44 %
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45 %Output: (1) mssim: the mean SSIM index value between 2 images.
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46 % If one of the images being compared is regarded as
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47 % perfect quality, then mssim can be considered as the
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48 % quality measure of the other image.
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49 % If img1 = img2, then mssim = 1.
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50 % (2) ssim_map: the SSIM index map of the test image. The map
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51 % has a smaller size than the input images. The actual size:
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52 % size(img1) - size(window) + 1.
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53 %
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54 %Default Usage:
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55 % Given 2 test images img1 and img2, whose dynamic range is 0-255
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56 %
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57 % [mssim ssim_map] = ssim_index(img1, img2);
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58 %
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59 %Advanced Usage:
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60 % User defined parameters. For example
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61 %
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62 % K = [0.05 0.05];
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63 % window = ones(8);
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64 % L = 100;
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65 % [mssim ssim_map] = ssim_index(img1, img2, K, window, L);
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66 %
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67 %See the results:
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68 %
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69 % mssim %Gives the mssim value
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70 % imshow(max(0, ssim_map).^4) %Shows the SSIM index map
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71 %
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72
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73 % Removed dependency on Image Processing Toolbox -
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74 % Centre for Digital Music, Queen Mary, University of London.
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75 % This file copyright 2011 Ivan Damnjanovic.
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76 %========================================================================
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77
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78
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79 if (nargin < 2 || nargin > 5)
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80 ssim_index = -Inf;
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81 ssim_map = -Inf;
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82 return;
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83 end
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84
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85 if (size(img1) ~= size(img2))
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86 ssim_index = -Inf;
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87 ssim_map = -Inf;
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88 return;
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89 end
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90
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91 [M N] = size(img1);
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92
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93 if (nargin == 2)
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94 if ((M < 11) || (N < 11))
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95 ssim_index = -Inf;
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96 ssim_map = -Inf;
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97 return
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98 end
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99 % window = fspecial('gaussian', 11, 1.5); %
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100 %
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101 % Image Processing toolboxdependency
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102 % - fspecial function is from IMP toolbox
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103 % 2 - ways to do
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104 % a)
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105 % [wx,wy] = meshgrid(-5:5, -5:5);
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106 % window = exp(-(wx.*wx + wy.*wy)/4.5);
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107 % window = window/sum(window(:));
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108 % b)
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109 window = [1.05756559815326e-06,7.81441153305360e-06,3.70224770827489e-05,0.000112464355116679,0.000219050652866017,0.000273561160085806,0.000219050652866017,0.000112464355116679,3.70224770827489e-05,7.81441153305360e-06,1.05756559815326e-06;...
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110 7.81441153305360e-06,5.77411251978637e-05,0.000273561160085806,0.000831005429087199,0.00161857756253439,0.00202135875836257,0.00161857756253439,0.000831005429087199,0.000273561160085806,5.77411251978637e-05,7.81441153305360e-06;...
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111 3.70224770827489e-05,0.000273561160085806,0.00129605559384320,0.00393706926284679,0.00766836382523672,0.00957662749024029,0.00766836382523672,0.00393706926284679,0.00129605559384320,0.000273561160085806,3.70224770827489e-05;...
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112 0.000112464355116679,0.000831005429087199,0.00393706926284679,0.0119597604100370,0.0232944324734871,0.0290912256485504,0.0232944324734871,0.0119597604100370,0.00393706926284679,0.000831005429087199,0.000112464355116679;...
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113 0.000219050652866017,0.00161857756253439,0.00766836382523672,0.0232944324734871,0.0453713590956603,0.0566619704916846,0.0453713590956603,0.0232944324734871,0.00766836382523672,0.00161857756253439,0.000219050652866017;...
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114 0.000273561160085806,0.00202135875836257,0.00957662749024029,0.0290912256485504,0.0566619704916846,0.0707622377639470,0.0566619704916846,0.0290912256485504,0.00957662749024029,0.00202135875836257,0.000273561160085806;...
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115 0.000219050652866017,0.00161857756253439,0.00766836382523672,0.0232944324734871,0.0453713590956603,0.0566619704916846,0.0453713590956603,0.0232944324734871,0.00766836382523672,0.00161857756253439,0.000219050652866017;...
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116 0.000112464355116679,0.000831005429087199,0.00393706926284679,0.0119597604100370,0.0232944324734871,0.0290912256485504,0.0232944324734871,0.0119597604100370,0.00393706926284679,0.000831005429087199,0.000112464355116679;...
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117 3.70224770827489e-05,0.000273561160085806,0.00129605559384320,0.00393706926284679,0.00766836382523672,0.00957662749024029,0.00766836382523672,0.00393706926284679,0.00129605559384320,0.000273561160085806,3.70224770827489e-05;...
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118 7.81441153305360e-06,5.77411251978637e-05,0.000273561160085806,0.000831005429087199,0.00161857756253439,0.00202135875836257,0.00161857756253439,0.000831005429087199,0.000273561160085806,5.77411251978637e-05,7.81441153305360e-06;...
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119 1.05756559815326e-06,7.81441153305360e-06,3.70224770827489e-05,0.000112464355116679,0.000219050652866017,0.000273561160085806,0.000219050652866017,0.000112464355116679,3.70224770827489e-05,7.81441153305360e-06,1.05756559815326e-06];
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120 K(1) = 0.01; % default settings
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121 K(2) = 0.03; %
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122 L = 255; %
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123 end
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124
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125 if (nargin == 3)
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126 if ((M < 11) || (N < 11))
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127 ssim_index = -Inf;
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128 ssim_map = -Inf;
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129 return
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130 end
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131 % window = fspecial('gaussian', 11, 1.5); %
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132 %
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133 % Image Processing toolboxdependency
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134 % - fspecial function is from IMP toolbox
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135 % 2 - ways to do
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136 % a)
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137 % [wx,wy] = meshgrid(-5:5, -5:5);
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138 % window = exp(-(wx.*wx + wy.*wy)/4.5);
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139 % window = window/sum(window(:));
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140 % b)
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141 window = [1.05756559815326e-06,7.81441153305360e-06,3.70224770827489e-05,0.000112464355116679,0.000219050652866017,0.000273561160085806,0.000219050652866017,0.000112464355116679,3.70224770827489e-05,7.81441153305360e-06,1.05756559815326e-06;...
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142 7.81441153305360e-06,5.77411251978637e-05,0.000273561160085806,0.000831005429087199,0.00161857756253439,0.00202135875836257,0.00161857756253439,0.000831005429087199,0.000273561160085806,5.77411251978637e-05,7.81441153305360e-06;...
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143 3.70224770827489e-05,0.000273561160085806,0.00129605559384320,0.00393706926284679,0.00766836382523672,0.00957662749024029,0.00766836382523672,0.00393706926284679,0.00129605559384320,0.000273561160085806,3.70224770827489e-05;...
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144 0.000112464355116679,0.000831005429087199,0.00393706926284679,0.0119597604100370,0.0232944324734871,0.0290912256485504,0.0232944324734871,0.0119597604100370,0.00393706926284679,0.000831005429087199,0.000112464355116679;...
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145 0.000219050652866017,0.00161857756253439,0.00766836382523672,0.0232944324734871,0.0453713590956603,0.0566619704916846,0.0453713590956603,0.0232944324734871,0.00766836382523672,0.00161857756253439,0.000219050652866017;...
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146 0.000273561160085806,0.00202135875836257,0.00957662749024029,0.0290912256485504,0.0566619704916846,0.0707622377639470,0.0566619704916846,0.0290912256485504,0.00957662749024029,0.00202135875836257,0.000273561160085806;...
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147 0.000219050652866017,0.00161857756253439,0.00766836382523672,0.0232944324734871,0.0453713590956603,0.0566619704916846,0.0453713590956603,0.0232944324734871,0.00766836382523672,0.00161857756253439,0.000219050652866017;...
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148 0.000112464355116679,0.000831005429087199,0.00393706926284679,0.0119597604100370,0.0232944324734871,0.0290912256485504,0.0232944324734871,0.0119597604100370,0.00393706926284679,0.000831005429087199,0.000112464355116679;...
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149 3.70224770827489e-05,0.000273561160085806,0.00129605559384320,0.00393706926284679,0.00766836382523672,0.00957662749024029,0.00766836382523672,0.00393706926284679,0.00129605559384320,0.000273561160085806,3.70224770827489e-05;...
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150 7.81441153305360e-06,5.77411251978637e-05,0.000273561160085806,0.000831005429087199,0.00161857756253439,0.00202135875836257,0.00161857756253439,0.000831005429087199,0.000273561160085806,5.77411251978637e-05,7.81441153305360e-06;...
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151 1.05756559815326e-06,7.81441153305360e-06,3.70224770827489e-05,0.000112464355116679,0.000219050652866017,0.000273561160085806,0.000219050652866017,0.000112464355116679,3.70224770827489e-05,7.81441153305360e-06,1.05756559815326e-06];
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152 L = 255;
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153 if (length(K) == 2)
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154 if (K(1) < 0 || K(2) < 0)
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155 ssim_index = -Inf;
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156 ssim_map = -Inf;
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157 return;
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158 end
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159 else
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160 ssim_index = -Inf;
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161 ssim_map = -Inf;
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162 return;
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163 end
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164 end
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165
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166 if (nargin == 4)
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167 [H W] = size(window);
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168 if ((H*W) < 4 || (H > M) || (W > N))
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169 ssim_index = -Inf;
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170 ssim_map = -Inf;
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171 return
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172 end
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173 L = 255;
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174 if (length(K) == 2)
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175 if (K(1) < 0 || K(2) < 0)
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176 ssim_index = -Inf;
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177 ssim_map = -Inf;
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178 return;
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179 end
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180 else
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181 ssim_index = -Inf;
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182 ssim_map = -Inf;
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183 return;
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184 end
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185 end
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186
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187 if (nargin == 5)
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188 [H W] = size(window);
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189 if ((H*W) < 4 || (H > M) || (W > N))
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190 ssim_index = -Inf;
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191 ssim_map = -Inf;
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192 return
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193 end
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194 if (length(K) == 2)
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195 if (K(1) < 0 || K(2) < 0)
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196 ssim_index = -Inf;
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197 ssim_map = -Inf;
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198 return;
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199 end
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200 else
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201 ssim_index = -Inf;
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202 ssim_map = -Inf;
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203 return;
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204 end
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205 end
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206
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207 C1 = (K(1)*L)^2;
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208 C2 = (K(2)*L)^2;
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209 window = window/sum(sum(window));
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210 img1 = double(img1);
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211 img2 = double(img2);
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212
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213 mu1 = filter2(window, img1, 'valid');
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214 mu2 = filter2(window, img2, 'valid');
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215 mu1_sq = mu1.*mu1;
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216 mu2_sq = mu2.*mu2;
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217 mu1_mu2 = mu1.*mu2;
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218 sigma1_sq = filter2(window, img1.*img1, 'valid') - mu1_sq;
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219 sigma2_sq = filter2(window, img2.*img2, 'valid') - mu2_sq;
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220 sigma12 = filter2(window, img1.*img2, 'valid') - mu1_mu2;
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221
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222 if (C1 > 0 & C2 > 0)
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223 ssim_map = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))./((mu1_sq + mu2_sq + C1).*(sigma1_sq + sigma2_sq + C2));
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224 else
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225 numerator1 = 2*mu1_mu2 + C1;
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226 numerator2 = 2*sigma12 + C2;
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227 denominator1 = mu1_sq + mu2_sq + C1;
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228 denominator2 = sigma1_sq + sigma2_sq + C2;
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229 ssim_map = ones(size(mu1));
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230 index = (denominator1.*denominator2 > 0);
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231 ssim_map(index) = (numerator1(index).*numerator2(index))./(denominator1(index).*denominator2(index));
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232 index = (denominator1 ~= 0) & (denominator2 == 0);
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233 ssim_map(index) = numerator1(index)./denominator1(index);
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234 end
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235
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236 mssim = sum(ssim_map(:), [], 'double')/numel(ssim_map);
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237
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238 return |