An Optimal and Statistically Robust Correlation Technique for Block Based Motion Estimation

In this paper we propose an optimal and robust correlation technique for the local motion estimation purposes. It is based on the maximization of a statistical robust matching function, which is computed in the frequency domain and therefore can be implemented by fast transformation algorithms. We show that our method achieves a significant speed up and robustness over the full search block-matching algorithm. We also present a comparative performance analysis, which shows that the proposed method greatly outperforms the state-of-the-art in correlation motion estimation.