Image preprocessing to enhance phase correlation of featureless images

Traditional discussions of phase correlation for image registration consider the usefulness of the technique for feature-rich images and generally restrict image shifts to small percentages of the image size. When applied to featureless images, in applications such as cloud tracking, the phase correlation output is degraded by a prominent noise component, which is not predicted by the fundamental mathematical expression for phase correlation. In this work, an additional term is proposed in the mathematical description of input images, and expressions for the phase correlation under a variety of situations are developed in this manner. Based on the mathematical expressions, several image pre-processing approaches are proposed to improve phase correlation results for featureless imagery. A large set of sky images is used to represent the featureless image category and phase correlation results are analyzed for each proposed pre-processing technique and compared to the basic phase correlation algorithm. Results show dramatic enhancements in phase correlation results.