A minimum-entropy procedure for robust motion estimation

We focus on motion estimation using a block matching approach and suggest using a minimum-entropy criterion. Many entropy-based estimation procedures exist, such as plug-in estimators based on Parzen windowing. We consider here an alternative that is applicable to data of any dimension and that circumvents the critical issues raised by kernel-based methods. To the best of our knowledge, this criterion has not yet been considered for image processing problems. The inherent robustness property of entropy is expected to provide a robust and efficient estimation of the motion vector of a block of a video sequence. In particular, the minimum-entropy estimator should be robust to occlusions and variations of luminance, for which standard approaches like SSD usually meet their limitations.