This smells like homework, but I'll bite. It's unclear what the variables you've defined mean. What is the undefined variable W? What is 'length'? How does that differ from 'Len'? I'm not inclined to try to deciper indexing problems, but I'll offer an example.
This is an edited excerpt from a routine I used for grayscale dilation. In its original form, this replicates the behavior of imdilate(). It can be adapted to be a median or range filter. Maybe it will be of use.
% you'll have to figure out how you want to handle class dependency
% i'm just going to work in the input class
inclass=class(inpict);
% we need to know the size of the implied rectangular strel
sse=[5 5];
% i'm going to handle edges by padding them
% that way the output image is the same size.
% if you don't want to pad, you'll have to handle your indexing accordingly
padsize=floor(sse/2);
% if you don't want to use padarray, you can do this by
% generating padding blocks and concatenating them to the image
% if you don't want padding, you'll have to adjust your subscript ranges
s0=size(inpict);
inpict=padarray(inpict,padsize,'replicate','both');
s=size(inpict);
% preallocate the output array so you have somewhere to put the result
outpict=zeros(s0,inclass);
% specify offsets based on size of strel
osm=sse(1)-1;
osn=sse(2)-1;
% i'm assuming that the image is only 2D
for n=1:s0(2)
for m=1:s0(1)
% extract the sample region from the image
sample=inpict(m:(m+osm),n:(n+osn));
% since i'm doing dilation, this is essentially a maximum filter
% if you want to make a median filter, take the median instead
outpict(m,n)=max(sample(:));
end
end
% there really isn't anything else to do
