An 8×8-block based motion estimation using Kalman filter

It is now quite common in the pel-recursive approaches for motion estimation, to find applications of the Kalman filtering technique both in time and frequency domains. In the block-based approach, very few approaches are available of this technique to refine the estimation of motion vectors resulting from fast algorithms such as the three step on a 16×16-block basis. This paper proposes 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 previous 16×16-block based Kalman application of Kuo et al. (1996). The state-space representation uses a first order auto-regressive model. Comparative results obtained for different classes of video sequences are presented