Presentation + Paper
21 August 2020 A comparative performance evaluation of VP9, x265, SVT-AV1, VVC codecs leveraging the VMAF perceptual quality metric
Author Affiliations +
Abstract
The prevalence of video driven applications, leveraging over the top video on demand services as well as live video streaming applications, dominate network traffic over today’s internet landscape. As such, they necessitate efficient video compression methods to accommodate the desired quality of service and hence user experience. In this study, we compare the performances of the emerging versatile video coding (VVC) standard, the recently released AV1 encoder (using SVTAV1 instance), the established high efficiency video coding (HEVC) standard via its x265 implementation, and the earlier VP9 codec. We used selected videos coming from three different datasets, namely UT LIVE (432p), and HEVC test sequences (480p, 720p, 1080p) that provide diversity in video content, video resolutions, and frame rates. The experimental setup involved fixed quality encoding using four different rate points, and more specifically, QP values of 27, 35, 46, 55 for AV1 and VP9 and QP values of 22, 27, 32, 37 for VVC and x265 codecs. For estimating bitrate gains, we used the BD-RATE algorithm using both PSNR and VMAF for objective video quality assessment (VQA). We found that VVC achieved the best video coding performance, significantly outperforming all other codecs. AV1 consistently outperformed x265, but with narrow margins in some video sequences, suggesting that a cautious selection between the two codecs needs to based on application-specific criteria. Within the group of considered codecs, VP9 required the highest bitrates. Ongoing work involves extending the examined video datasets pool to different resolutions (e.g., 240p, 1600p) while investigating the correlation between subjective and objective VQA scores.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gangadharan Esakki, Andreas Panayides, Sravani Teeparthi, and Marios Pattichis "A comparative performance evaluation of VP9, x265, SVT-AV1, VVC codecs leveraging the VMAF perceptual quality metric", Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 1151010 (21 August 2020); https://doi.org/10.1117/12.2567392
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Video

Video compression

Computer programming

Video coding

Internet

Zoom lenses

Subjective video quality evaluation

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