Just open up entropy() or look at the docs to see how it works.
% just grab some image and make it into an example
inpict = imread('cameraman.tif'); % this is uint8
inpict = im2uint16(inpict); % make it uint16
% process it to move the data outside of 2^8 locations
inpict = imfilter(inpict,fspecial('disk',3));
% this is what entropy() does
counts = imhist(inpict(:),2^16);
numel(counts) % it's using 65536 bins
counts = counts(counts~=0); % get rid of empty bins
numel(counts) % how many bins are left?
counts = counts/numel(inpict); % normalize the sum
E = -sum(counts.*log2(counts)) % this is the result with 65536 bins
F = entropy(inpict) % this is the result with 256 bins
For illustrative purposes, try commenting out the imfilter() line and see what happens to the bin counts and the relationship between E and F.
