It is a locally adaptive filter that ensure that within every specified window, the mean and the contrast match some given values. It is great to get rid of uneven illumination, I use it mostly for microscopy image preprocessing. Here's an implementation, sorry for lack of documentation.
obj.output is image,
Md and Dd are mean and contrast to match,
Amax and p constrain the change in individual pixels,
W is window size.
function WallisFilter(obj, Md, Dd, Amax, p, W, varargin )
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
if mod(W,2)==0
W = W+1;
end
w = floor(W/2);
F = double(obj.output);
if size(varargin) > 0
if varargin{1} == 1
% gauss_blur = 1/273 * [1 4 7 4 1; 4 16 26 16 4; 7 26 41 26 7; 4 16 26 16 4; 1 4 7 4 1];
% F = conv2(F, gauss_blur, 'same');
gauss_blur = fspecial('gaussian', W, 1);
F = conv2(F, gauss_blur, 'same');
end
end
convNumEl = ones(size(F));
M = conv2(F,ones(W),'same')./conv2(convNumEl,ones(W),'same');
D = (conv2((F-M).^2,ones(W),'same')/(W^2)).^0.5;
G = (F-M) .* Amax .* Dd ./ (Amax .* D + Dd) + p * Md + (1-p) * M;
G(G<0) = 0;
G(G>65534) = 65534;
obj.output = uint16(G);
end
