Adaptive Progressive Motion Vector Resolution Selection Based on Rate-Distortion Optimization

Abstract

In the state-of-the-art H.265/HEVC video coding standard, the motion vector (MV) resolution is fixed to be 1/4-pel for the entire video sequence, while the inherent video characteristics, e.g. texture complexities and motion activities have been largely ignored. Obviously such strategy may not suffice the demand of high-accuracy motion compensation. In this paper, we propose a specially designed rate-distortion model in terms of the MV resolution by taking the video characteristics into consideration. In particular, the MV resolution selection is formulated as a rate-distortion optimization problem by analyzing the rate-distortion cost of each MV resolution candidate. To further improve the coding performance, the progressive MV resolution strategy is employed, where the optimal progressive MV resolution is determined by decision trees constructed with the rate-distortion model. In this manner, a novel adaptive progressive motion vector resolution (APMVR) selection scheme can be realized and the MV resolution can be adaptively adjusted based on the properties of local content. Extensive experimentsand comparisons show that the proposed algorithm significantly improves the coding performance, and 1.8% BD-rate gain onaverage has been achieved without introducing any noticeable computational complexity.

Existing System

Proposed System

Architecture