How do we computer SSD (Sum of Squared Differences)
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Hello!
I am having two images f and g, where g contains a block which is also present in a. How can detect the block in a using SSd? How is SSD computed. Please help!
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Matt J
il 20 Set 2014
If g is a template of the block you're searching for, the minimum SSD match is equivalent to the maximum non-normalized correlation match,
correlation=conv2(f,rot90(g,2),'same');
[i,j]=find(correlation=max(correlation(:)));
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Mohammad Al Nagdawi
il 29 Lug 2018
from the best on my knowledge the state of the art similarity measure unable to find similarity for such images that will lead to correct registration. I tried Mutual information, Jefferey divergence. conv2, RMSE, and PSNR are helpful only for monomodal images. Can you suggest a nonexistent solution I will build and try?
Image Analyst
il 29 Lug 2018
Then you'll have to develop your own. One that preprocesses the images to get something that can be used for registration, like one that finds the outer circle and center, and being robust enough to handle that gradient.
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Image Analyst
il 20 Set 2014
Didn't I answer that in your other question http://www.mathworks.com/matlabcentral/answers/155574#comment_238296
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