Layer-Adaptive Mode Decision and Motion Search for Scalable Video Coding with Combined Coarse Granular Scalability (CGS) and Temporal Scalability

摘要

In this paper, we propose a layer-adaptive mode decision algorithm and a motion search scheme for the scalable video coding (SVC) with combined coarse granular scalability (CGS) and temporal scalability. To speed up the encoder while minimizing the loss in coding efficiency, our layer-adaptive mode decision recursively refers to the prediction modes and quantization parameter of the reference/base layer to minimize the number of modes tested at the enhancement layer. Moreover, our motion search scheme adaptively reuses the reference frame indices of the base layer and determines the initial search point using the motion vector at the base layer or the motion vector predictor at the enhancement layer. As compared with JSVM 8, the proposed algorithms provide up to 75% overall time saving and more than 85% time reduction for encoding enhancement layers with negligible loss in coding efficiency.