Modified Frequency-tuned Saliency

beginT = cputime;
%---------------------------------------------------------
% Copyright (c) 2009 Radhakrishna Achanta [EPFL]
% Contact: firstname.lastname@epfl.ch
%---------------------------------------------------------
% Citation:
% @InProceedings{LCAV-CONF-2009-012,
%    author      = {Achanta, Radhakrishna and Hemami, Sheila and Estrada,
%                  Francisco and S�sstrunk, Sabine},
%    booktitle   = {{IEEE} {I}nternational {C}onference on {C}omputer
%                  {V}ision and {P}attern {R}ecognition},
%    year        = 2009
% }
%---------------------------------------------------------
% Please note that the saliency maps generated using this
% code may be slightly different from those of the paper.
% This seems to be because the RGB to Lab conversion is
% different from the one used for the results in the C++ code.
% The C++ code is available on the same page as this matlab
% code (http://ivrg.epfl.ch/supplementary_material/RK_CVPR09/index.html)
% One should preferably use the C++ as reference and use
% this matlab implementation mostly as proof of concept
% demo code.
%---------------------------------------------------------
% Read image and blur it with a 3x3 or 5x5 Gaussian filter
%---------------------------------------------------------
img = imread('../dog.jpg');%Provide input image path
gfrgb = imfilter(img, fspecial('gaussian', 3, 3), 'symmetric', 'conv');
%---------------------------------------------------------
% Perform sRGB to CIE Lab color space conversion (using D65)
%---------------------------------------------------------
%cform = makecform('srgb2lab', 'AdaptedWhitePoint', whitepoint('d65'));
%lab = applycform(gfrgb,cform);
R = gfrgb(:,:,1);
G = gfrgb(:,:,2);
B = gfrgb(:,:,3);
%lab = gfrgb;
%lab = RGB2Lab(R,G,B);
%---------------------------------------------------------
% Compute Lab average values (note that in the paper this
% average is found from the unblurred original image, but
% the results are quite similar)

%MEAN   Average or mean value.
%   S = MEAN(X) is the mean value of the elements in X
%   if X is a vector. For matrices, S is a row
%   vector containing the mean value of each column.
%   For N-D arrays, S is the mean value of the
%   elements along the first array dimension whose size
%   does not equal 1.
%   If X is floating point, that is double or single,
%   S has the same class as X. If X is of integer
%   class, S has class double.

%---------------------------------------------------------
%l = double(lab(:,:,1)); lm = mean(mean(l));
%a = double(lab(:,:,2)); am = mean(mean(a));
%b = double(lab(:,:,3)); bm = mean(mean(b));
gm = mean(mean(G));
%---------------------------------------------------------
% Finally compute the saliency map and display it.

% Euclidean Distance
%---------------------------------------------------------
sm = 1-(G-gm);
%sm = (l-lm).^2 + (a-am).^2 + (b-bm).^2;
imshow(sm,[]);
%---------------------------------------------------------
endT = cputime - beginT;