A stochastic optimization scheme for automatic registration of aerial images

The topic of this work is related to image registration of aerial images. This topic represents a very complicated problem especially when several variations and distortions occur. In addition to that, the requirement for an automated process further complicates this task. In this paper a stochastic optimization scheme is proposed using genetic algorithms to address misalignments caused by viewpoint, temporal and terrain variations of aerial images. A multiscale optical flow approach is applied next to achieve subpixel registration. Some experimental results are also presented to indicate the applicability of the proposed scheme.