A rate-distortion analysis on motion prediction efficiency and mode decision for scalable wavelet video coding

A rate-distortion model for describing the motion prediction efficiency in interframe wavelet video coding is proposed in this paper. Different from the non-scalable video coding, the scalable wavelet video coding needs to operate under multiple bitrate conditions and it has an open-loop structure. The conventional Lagrangian multiplier, which is widely used to solve the rate-distortion optimization problems in video coding, does not fit well into the scalable wavelet structure. In order to find the rate-distortion trade-off due to different bits allocated to motion and textual information, we suggest a motion information gain (MIG) metric to measure the motion prediction efficiency. Based on this metric, a new cost function for mode decision is proposed. Compared with the conventional Lagrangian method, our experiments show that the proposed method is less extraction-bitrate dependent and generally improves both the PSNR performance and the visual quality for the scalability cases.

Research highlights
► A new rate-distortion metric proposed to measure the motion prediction efficiency in video coding.
► The new mode decision method is less extraction-bitrate dependent.
► The proposed cost function matches the scalable wavelet video codec structure better than the Lagrangian cost function.
► A highly efficient parameter selection algorithm for scalable wavelet video coding.