Low complexity encoder optimization for HEVC

• Published in: Journal of visual communication and image representation Vol. 35; pp. 120 - 131
• Main Authors: Wang, Shanshe, Luo, Falei, Ma, Siwei, Zhang, Xiang, Wang, Shiqi, Zhao, Debin, Gao, Wen
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.02.2016
• Subjects: Coders; Coding; Complexity; Computation; CU splitting; Encoder optimization; Encoders; HEVC; Intra mode decision; Low complexity; Optimization; Rate distortion optimization; Reduction; Reference frame selection; Video coding; Video compression; Video coding; Intra mode decision; Rate distortion optimization; Reference frame selection; HEVC; Low complexity; CU splitting; Encoder optimization
• ISSN: 1047-3203; 1095-9076
• DOI: 10.1016/j.jvcir.2015.12.005

•Considering the content characteristic of different PU, an optimization scheme is proposed.•Based on the R–D cost distribution, an early termination scheme of coding unit (CU) splitting is proposed.•Based on the reference frame distribution, an adaptive reference frame selection scheme is proposed. High Efficiency Video Coding (HEVC) improved the coding efficiency significantly. Compared to its predecessor H.264/AVC, it can provide equivalent subjective quality with more than 57% bit rate reduction. However, the improvement on coding efficiency is obtained at the expense of much more intensive computation complexity. In this paper, based on an overall analysis of computation complexity at the HEVC encoder, a low complexity encoder optimization scheme is proposed by reducing the number of available candidates for evaluation in terms of the intra prediction mode decision, early termination of coding unit (CU) splitting and adaptive reference frame selection. With the proposed scheme, the rate distortion optimization (RDO) technique of HEVC can be implemented in a low-complexity way for complexity-constrained encoders. Experimental results demonstrate that, compared with the original HEVC reference encoder implementation, the proposed optimization scheme can achieve more than 40% complexity reduction on average with coding performance degradation as only 0.43% which can be ignorable.