A sift-based mode-seeking procedure for efficient, accurate registration of remotely sensed images

Several image registration methods, based on the scaled-invariant feature transform (SIFT) technique, have appeared recently in the remote sensing literature. All of these methods attempt to overcome problems encountered by SIFT in multi-modal remotely sensed imagery, in terms of the quality of its feature correspondences. The method presented in this paper performs mode seeking (in transformation space) to eliminate outlying corresponding key-points (i.e., features) and improve the overall match obtained. Preliminary experimental results seem to indicate that our method achieves high accuracy and is rather fast in a variety of test cases.