This question is related to these two:
http://stackoverflow.com/questions/2867901/introduction-to-vectorizing-in-matlab-any-good-tutorials
http://stackoverflow.com/questions/2561617/filter-that-uses-elements-from-two-arrays-at-the-same-time

Basing on the tutorials I read, I was trying to vectorize some procedure that takes really a lot of time.

I've rewritten this:

function B = bfltGray(A,w,sigma_r)
dim = size(A);
B = zeros(dim);
for i = 1:dim(1)
    for j = 1:dim(2)

        % Extract local region.
        iMin = max(i-w,1);
        iMax = min(i+w,dim(1));
        jMin = max(j-w,1);
        jMax = min(j+w,dim(2));
        I = A(iMin:iMax,jMin:jMax);

        % Compute Gaussian intensity weights.
        F = exp(-0.5*(abs(I-A(i,j))/sigma_r).^2);
        B(i,j) = sum(F(:).*I(:))/sum(F(:));

    end
end

into this:

function B = rngVect(A, w, sigma)
W = 2*w+1;
I = padarray(A, [w,w],'symmetric');
I = im2col(I, [W,W]);
H = exp(-0.5*(abs(I-repmat(A(:)', size(I,1),1))/sigma).^2);
B = reshape(sum(H.*I,1)./sum(H,1), size(A, 1), []);

But this version seems to be as slow as the first one, but in addition it uses a lot of memory and sometimes causes memory problems.

I suppose I've made something wrong. Probably some logic mistake regarding vectorizing. Well, in fact I'm not surprised - this method creates really big matrices and probably the computations are proportionally longer.

I have also tried to write it using nlfilter (similar to the second solution given by Jonas) but it seems to be hard since I use Matlab 6.5 (R13) (there are no sophisticated function handles available).

So once again, I'm asking not for ready solution, but for some ideas that would help me to solve this in reasonable time. Maybe you will point me what I did wrong.