Multi-temporal image registration utilizing a differential evolution algorithm with replacement strategy

Image registration is effect by finding the best spatial transformation between the reference image and the floating image in terms of optimizing a similarity metric. Mutual information, as an effective method, is a reliable criterion for image registration. In this paper, we propose an improved differential evolution algorithm with replacement strategy to maximize the mutual information for multi-temporal image registration. Experimental results show that our new algorithm achieves more precise and robust results when compared with several other classical optimization methods.