A new SIFT matching criteria in a genetic algorithm framework for registering multisensory satellite imagery

Abstract

Synthetic Aperture Radar (SAR) images are efficient and reliable source of information in extraction of damaged regions in case of floods. In assessment of damage accurately due to floods, image registration of optical (before-flood) and SAR images (after-flood) has to be carried out efficiently. In this paper, we discuss a robust multi-sensor image registration algorithm using scale invariant feature points for keypoint extraction. For matching the keypoints, a multi-objective genetic algorithm is developed with angle, distance and vicinity criterion as the fitness functions. This optimization process helps in matching the scale invariant feature points. From the obtained results, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient. Copyright 2014 ACM.