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Proceedings Paper

Compression performance of HEVC and its format range and screen content coding extensions
Author(s): Bin Li; Jizheng Xu; Gary J. Sullivan
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Paper Abstract

This paper presents a comparison-based test of the objective compression performance of the High Efficiency Video Coding (HEVC) standard, its format range extensions (RExt), and its draft screen content coding extensions (SCC). The current dominant standard, H.264/MPEG-4 AVC, is used as an anchor reference in the comparison. The conditions used for the comparison tests were designed to reflect relevant application scenarios and to enable a fair comparison to the maximum extent feasible – i.e., using comparable quantization settings, reference frame buffering, intra refresh periods, rate-distortion optimization decision processing, etc. It is noted that such PSNR-based objective comparisons generally provide more conservative estimates of HEVC benefit than are found in subjective studies. The experimental results show that, when compared with H.264/MPEG-4 AVC, HEVC version 1 provides a bit rate savings for equal PSNR of about 23% for all-intra coding, 34% for random access coding, and 38% for low-delay coding. This is consistent with prior studies and the general characterization that HEVC can provide about a bit rate savings of about 50% for equal subjective quality for most applications. The HEVC format range extensions provide a similar bit rate savings of about 13–25% for all-intra coding, 28–33% for random access coding, and 32–38% for low-delay coding at different bit rate ranges. For lossy coding of screen content, the HEVC screen content coding extensions achieve a bit rate savings of about 66%, 63%, and 61% for all-intra coding, random access coding, and low-delay coding, respectively. For lossless coding, the corresponding bit rate savings are about 40%, 33%, and 32%, respectively.

Paper Details

Date Published: 22 September 2015
PDF: 12 pages
Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 959919 (22 September 2015); doi: 10.1117/12.2193676
Show Author Affiliations
Bin Li, Microsoft Research Asia (China)
Jizheng Xu, Microsoft Research Asia (China)
Gary J. Sullivan, Microsoft Corp. (United States)


Published in SPIE Proceedings Vol. 9599:
Applications of Digital Image Processing XXXVIII
Andrew G. Tescher, Editor(s)

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