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Mutual information (MI) is one of the most popular and widely used similarity measures in image registration. In traditional registration processes, MI is computed in each optimization step to measure the similarity between the reference image and the moving image. The presumption is that whenever MI reaches its highest value, this corresponds to the best match. This paper shows that this presumption is not always valid and this leads to registration error. To overcome this problem, we proposedoi:10.11591/ijece.v11i3.pp2613-2620 fatcat:3zu6yknigjhhpca76h53b5kg6y