Information divergence measure for ISAR image registration

Entropy-based divergence measures have shown promising results in many areas of engineering and image processing. In this paper, a new generalized divergence measure, divergence, is proposed. Some properties such as convexity and its upper bound are derived. Based on the Jensen-Renyi divergence, we propose a new approach to the problem of ISAR (Inverse Synthetic Aperture Radar) image registration. The goal is to estimate the target motion during the imaging time. Our approach applies Jensen-Renyi divergence to measure the statistical dependence between consecutive ISAR image frames, which would be maximal if the images are geometrically aligned. Simulation results demonstrate that the proposed method is efficient and effective.