| function output = prefilt(img, fc) | |
| % ima = prefilt(img, fc); | |
| % fc = 4 (default) | |
| % | |
| % Input images are double in the range [0, 255]; | |
| % You can also input a block of images [ncols nrows 3 Nimages] | |
| % | |
| % For color images, normalization is done by dividing by the local | |
| % luminance variance. | |
| if nargin == 1 | |
| fc = 4; % 4 cycles/image | |
| end | |
| w = 5; | |
| s1 = fc/sqrt(log(2)); | |
| % Pad images to reduce boundary artifacts | |
| img = log(img+1); | |
| img = padarray(img, [w w], 'symmetric'); | |
| [sn, sm, c, N] = size(img); | |
| n = max([sn sm]); | |
| n = n + mod(n,2); | |
| img = padarray(img, [n-sn n-sm], 'symmetric','post'); | |
| % Filter | |
| [fx, fy] = meshgrid(-n/2:n/2-1); | |
| gf = fftshift(exp(-(fx.^2+fy.^2)/(s1^2))); | |
| gf = repmat(gf, [1 1 c N]); | |
| % Whitening | |
| output = img - real(ifft2(fft2(img).*gf)); | |
| clear img | |
| % Local contrast normalization | |
| localstd = repmat(sqrt(abs(ifft2(fft2(mean(output,3).^2).*gf(:,:,1,:)))), [1 1 c 1]); | |
| output = output./(.2+localstd); | |
| % Crop output to have same size than the input | |
| output = output(w+1:sn-w, w+1:sm-w,:,:); | |