Optimizing Rate Control Performance for Scalable Video Coding

Scalable Video Coding (SVC) has recently attracted much attention due to the increasing need of delivering reliable video transmissions to diverse clients over heterogeneous networks. SVC encodes the video signal once, but enables decoding from partial streams depending on the specific rate and resolution required by a specific application, particularly in scenarios where the downstream client capabilities, system resources and network conditions are not known in advance. SVC is currently developed as an extension of the H.264/AVC by utilizing the temporal layer, spatial layer and quality layer. The extremely complex coding structure of SVC makes Rate Control (RC), which aims to maximize the compression performance given the transmission capacity limit, a very challenging task. In this research, the researchers propose two research aspects to optimize the RC performance for SVC. Firstly, the bit allocation scheme will be explored to effectively distribute bit budgets among different coding granularities in order to achieve the best video quality, which can also be used to optimize bitstream extraction for transmission. Secondly, the bit allocation achievement method is proposed to achieve the target bits for each coding unit by selecting appropriate quantization parameters. This research will further boost the application of SVC for internet video, live broadcast, etc.