Application of multiresolution wavelet pyramids and gradient search based on mutual information to subpixel registration of multisensor satellite imagery

Accurate geometric registration is an important step that precedes various tasks of processing of remotely sensed imagery. Assuming that, after radiometric and systematic correction, images are registered to within a few pixels, our goal is to develop fast and reliable automatic registration methods for multi-sensor data that would yield sub-pixel accuracy. This paper compares two gradient-based algorithms for sub-pixel image registration developed by Thevenaz et al. One of them optimizes intensity difference while the other maximizes mutual information between two images. The algorithms were combined with three invariant wavelet pyramids, a centered cubic spline pyramid as well as both low-pass and band-pass Simoncelli Steerable pyramids. This paper compared the different variations of the two algorithms on both synthetic and real satellite imagery. We found that for single-sensor data, the intensity-based algorithm combined with a band-pass wavelet pyramid produces the best results, while for multi-sensor images, the best choice is the mutual-information-based method combined with a steerable low-pass pyramid.