Abstract
In this paper, an approach to medical image registration using Powell's algorithm with a basic concept from mutual information, & entropy, as a new matching criterion is presented. This approach uses histogram equalised reference image and target image. Volume control points of these enhanced images determine the quality of image registration. Based on these volume control points, features like location, edge pixel intensity strength & orientation are considered to compute a joint probability distribution of corresponding edge points from reference and target images. Then mutual information based on this function is minimised to find the best alignment parameters and the translation parameters are calculated using Powell's algorithm and matched to perform image registration. The proposed registration algorithm is faster, robust & proved to be more efficient than the ACO approach quantitatively. Simulations for Powell's algorithm using enhanced images of the same size but with different angles are shown here.
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