Is there an efficient and fast way to process pixel neighborhoods without loops?
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Hi all, I am looking for an efficient and fast way to process local window without loops. I want to apply a nonlinear operation on the local neighborhood with an exponential function. The output of this operation is not a scalar rather than being a weight for ever pixel in the neighborhoods. Later, I use these weights to calculate the final value of the central pixel. Here is a code snippet of what I did:
for i=1:r
for j=1:c
x=i:i+wsize-1; y=j:j+wsize-1 % wsize=3 (the window size)
if(max(x)>r || (max(y)>c))
break
end
Win=im1(x,y); Win=Win(:);
C=im2(x,y); C=C(:); % current window of size wsize
avgC=mean(C);
Gij=exp(-(C-(avgC(i,j)))./C);
Wij=(G_ij)./sum(G_ij);
im3(i,j)=sum(Win.*Wij);
end
end
Note: im1 and im2 are different while the desired output will be in im3.
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Answers (2)
Image Analyst
on 26 Jan 2016
There is a function called nlfilter() that can apply your custom function to a moving neighborhood. I attach a demo.
2 Comments
Tony Richardson
on 13 Jul 2020
I've written up a brief description (see the url below) of a fairly straight-forward method that I've found to be much faster that nlfilter. It does not use loops (vectorized) and still easily allows for non-linear processing of neighborhoods (for example - median processing). (nlfilter allows non-linear processing, but conv2 and imfilter do not.)
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