A Niche Based Genetic Algorithm for Image Registration

Image registration aims to find the unknown set of transformations able to reduce two or more images to a common reference frame. Image registration can be regarded as an optimization problem, where the goal is to maximize a measure of image similarity. The measure of similarity on the overall image can be computationally expensive, leading to measure the similarity of smaller subimages. However, the reduction of subimage size results into a higher multi-modality for the optimizing function. Recent investigations have shown that genetic algorithms can address this problem. However, the simple scheme of genetic algorithms can still fall in local optima. In this paper, we explore the application of niche-oriented genetic algorithms, showing their strengths in providing a more effective image registration algorithm.