GOP Structure-Independent Quantization Parameter Cascading in Video Coding

• Published in: IEEE access Vol. 7; pp. 76274 - 76282
• Main Authors: Xu, Yiwen, Yi, Shiqi, Lin, Liqun, Chen, Weiling, Zhao, Tiesong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bit rate; Coders; Coding standards; Distortion; Encoding; Frames (data processing); high efficiency video coding (H.265/HEVC); Measurement; Neural networks; Nonlinear distortion; Optimization; Parameters; Quantization (signal); quantization parameter (Qp); Random access; rate-distortion (RD); Resource management; Time dependence; Video coding; Video compression
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2922476

The popular lossy coding standards set unequal quantization parameter (Qp) values to its successive frames or slices aimed at minimizing its encoder distortion subject to a bitrate constraint. Nowadays, this Qp cascading (QPC) strategy is normally achieved by the derivation of an optimization problem with regard to the group-of-picture (GOP) structure of successive frames. In this paper, we propose to extract coding unit (CU)-level predicting information and project them to frame-level dependency with real-time neural networks. Thus, we successfully estimate and update the frame-level dependency in a GOP without prior knowledge to the GOP-level prediction structure. Finally, the dependency is utilized in adaptive QPC for diverse GOP structures. The experimental results on high efficiency video coding (H.265/HEVC) demonstrate the effectiveness of our proposed framework, which achieves adaptive QPC for both random access (RA) and low delay (LD) structures with superior rate-distortion (RD) performances.