Image Sequence Compression Using a Pel-Recursive Motion-Compensated Technique

This paper presents and analyzes a pel-recursive, motioncompensated, image sequence compression algorithm [1]. The analysis retains all the terms of the Taylor's series expansion and yields a set of equations for which the convergence criteria and the convergence rate of the motion estimate are more easily seen. The existing motion prediction schemes are also reviewed and a new motion prediction scheme is presented which is shown to be superior to the existing schemes. Simulations run on actual image sequences to verify the analytical results indicate that implementing the analytical model as opposed to the generally used heuristic technique does yield a decrease in the information rate and the computational requirements. Simulation results also are included which use the "projection-along-the-motiontrajectory" or PAMT prediction scheme. Third, zeroth-order entropy encoding is shown to reduce the bit rate on the order of 12 percent, and to reduce the mean square error in the reconstructed images on the order of 60 percent when compared to first-order entropy encoding. Fourth, field-to-field motion prediction is compared to frame-to-frame motion prediction.