Introducing GOP-level quantization parameter offset in high efficiency video coding
Linfeng Xu, Ce Zhu, Yimin Zhou, Yuxin Wang, Yansong Gao · 2016
Due to an extensive use of spatial-temporal prediction techniques, a large amount of the spatial-temporal dependency is incurred in video coding. To optimize coding performance in the block-based hybrid coding architecture, rate-distortion optimization (RDO) techniques are widely employed based on different levels ranging from frame-level to slice-level, to coding tree unit (CTU)-level, coding unit (CU)-level and prediction unit (PU)-level. However the dependency among groups of pictures (GOPs) has not been addressed. Through a statistical analysis of the reference dependency among GOPs under the Random-Access (RA) configuration in the High Efficiency Video Coding (HEVC) standard, we then develop a GOP-level Quantization Parameter (QP) optimization scheme to further enhance the coding performance. The experimental results justify effectiveness of our proposed scheme, where 0.96% Bj⊘ntegaard Delta rate (BD-rate) saving can be achieved on average with the RA configuration with a lower overall coding complexity, compared with the latest reference software HM 16.4 of HEVC standard.