局部对比度归一化层Local Contrast Normalization Layer-N
局部对比度归一化层Local Contrast Normalization Layer-N：可参考链接：http://blog.csdn.net/zouxy09/article/details/10007237
function y = localContrastNormalize(I, windowSize)
% Locally contrast normalizes an image. This is very often used as a
% pre-processing technique in feature learning. It is described in more
% detail in, for example,
%
% Jarett et al., "What is the Best Multi-Stage Architecture for Object
% Recognition?" (ICCV 2009)
%
% EXAMPLE
%G = rgb2gray(imread('data/lenna.jpg'));
%y = localContrastNormalize(G);
%figure(1); imshow(G,[]); figure(2); imshow(y,[]);
%
if(isa(I, 'uint8')), I = double(I) / 255.0; end
if nargin < 2 || isempty(windowSize), windowSize = 8; end
nd = ndims(I);
wSide = normpdf(linspace(-2, 2, windowSize), 0, 1);
w = wSide'*wSide;
w = w/sum(sum(w));
conv2opt= 'same';
% if removeBorder, conv2opt= 'full'; end
if nd == 2
% grayscale input
v = I - conv2(I, w, conv2opt);
s = sqrt(conv2(v.^2, w, conv2opt));
c = mean(mean(s));
y = v./max(c, s);
else
% RGB input
v1 = I(:,:,1) - conv2(I(:,:,1), w, conv2opt);
v2 = I(:,:,2) - conv2(I(:,:,2), w, conv2opt);
v3 = I(:,:,3) - conv2(I(:,:,3), w, conv2opt);
s = sqrt(conv2(v1.^2, w, conv2opt) + conv2(v2.^2, w, conv2opt) + conv2(v3.^2, w, conv2opt));
c = mean(mean(s));
mm= max(c, s);
y = cat(3, v1./mm, v2./mm, v3./mm);
end
end
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