Linear and non-linear filters for block based motion estimation

Many techniques are currently used for motion estimation. In the block-based approaches the most common procedure applied is the block matching based on various algorithms. To refine the motion estimates resulting from the full search or any coarse search algorithm, one can find few applications of Kalman filtering, mainly in the intraframe scheme. This paper presents an 8×8-block based motion estimation which uses the Kalman filtering technique to improve the motion estimates resulting from both the three step algorithm and the 16×16-block based Kalman application. In the interframe scheme, due to discontinuities in the dynamic behaviour of the motion vectors, we propose the filtering by approximated densities. This application uses a simple form involving statistical characteristics of multi-modal distributions