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How to combine normxcorr2 similarity results with single value, like mutual information?

Asked by Mohammad Al Nagdawi on 1 Nov 2017
Latest activity Edited by Mohammad Al Nagdawi on 2 Nov 2017
Hi everyone
I want a single value normalized cross-correlation similarity between two images while transforming. This value I want to compare with other similarity measures, such as mutual information.
for i = 50:step:end_rang
% horizantal transformation
[overlap_fix,overlap_float] = overlapArea(fix_img,float_img,i);
MI(2,ind) = size(overlap_fix,2);
MI(3,ind) = MutualInfo(overlap_fix,overlap_float,all_float_px,overlap_limit);
JD(ind) = jeffrey_divergence_Xu_paper(overlap_fix,overlap_float,all_float_px,overlap_limit);
if std(double(overlap_fix(:))) ~= 0
cc(ind) = sum(sum(normxcorr2(overlap_fix,overlap_float)))/numel(overlap_fix);
else
cc(ind) = 0;
disp(['skip ',num2str(i)]);
end
ind = ind +1;
end
The method I use to convert 'normxcorr2' output matrix to a single value, is it correct? where the identical images have the highest value

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