University of Houston

In this thesis, we present the image registration method using mutual information as the similarity measure. We introduce the important components that the image registration has: namely transformation model, optimization method, and similarity measure. We further look into the mutual information and its related background mathematically and theoretically. Also, Examples walking through the procedure of calculating mutual information are presented. Finally, comprehensive experiments are carried on. Both registrations using mutual information and correlation similarity are investigated.