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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Respuestas (2)
Image Analyst
el 26 de En. de 2016
There is a function called nlfilter() that can apply your custom function to a moving neighborhood. I attach a demo.
2 comentarios
Image Analyst
el 26 de En. de 2016
Just get rid of the loops and vectorize it. Use conv2() or imfilter().
Tony Richardson
el 13 de Jul. de 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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