An efficient SIFT-based mode-seeking algorithm for sub-pixel 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 multimodal remotely sensed imagery, in terms of the quality of its feature correspondences. The deterministic method presented in this letter exploits the fact that each SIFT feature is associated with a scale, orientation, and position to perform mode seeking (in transformation space) to eliminate outlying corresponding key points (i.e., features) and improve the overall match obtained. We also present an exhaustive empirical study on a variety of test cases, which demonstrates that our method is highly accurate and rather fast. The algorithm is capable of automatically detecting whether it succeeded or failed.