A Progressive Refinement Approach to Aerial Image Registration Using Local Transform Perturbations

Spatial domain log-polar approaches have demonstrated success for video image registration. However, the log-polar representation is sensitive to origin location. This drawback often necessitates performing a parameter sweep over log-polar origin location, which can be time-consuming. In this paper we present an alternative approach that is appropriate for small to moderate scale, rotational, and skew misalignments but allows large translational offset. We use a form of robust phase correlation to estimate the gross translation, then perform a local search over log-polar origin to fine tune the translation. We sequentially estimate affine transform parameters by maximizing a measure of registration solution verity. We also investigate the effect of scale and rotational initial alignment errors on the robustness of the initial phase correlation to estimate gross translation. We present results using video imagery acquired from a real aerial video surveillance system.