Rate-constrained motion estimation using Kalman filter

Abstract

The rate-constrained (R–D) motion estimation techniques have been presented to improve the conventional block-matching algorithm by using a joint rate and distortion criterion. This paper presents a new motion estimation algorithm using Kalman filter to improve the performance of the conventional R–D motion estimation at a relatively low computational cost. The Kalman filter exploits the correlation of block motion to achieve higher precision of motion estimation and compensation. In the proposed algorithm, the Kalman filter is embedded into the optimization process of R–D motion estimation by defining a new R–D criterion. Simulation results show that the new algorithm improves the rate–distortion performance significantly.