Convex-hull Estimation using XPSNR for Versatile Video Coding
Vignesh V Menon, Christian R. Helmrich, Adam Wieckowski, Benjamin, Bross, Detlev Marpe

TL;DR
This paper proposes using XPSNR as a perceptual quality metric for VVC, demonstrating its superior correlation with subjective quality and showing improvements in quality, encoding, and decoding times over traditional metrics.
Contribution
It introduces a convex-hull estimation method using XPSNR for optimized bitrate-resolution selection in VVC, enhancing streaming efficiency and perceptual quality.
Findings
XPSNR correlates better with subjective quality than VMAF for UHD VVC content.
The proposed convex-hull method improves quality by 5.84 dB PSNR and 0.62 dB XPSNR.
Encoding and decoding times are reduced by 44.43% and 65.46%, respectively.
Abstract
As adaptive streaming becomes crucial for delivering high-quality video content across diverse network conditions, accurate metrics to assess perceptual quality are essential. This paper explores using the eXtended Peak Signal-to-Noise Ratio (XPSNR) metric as an alternative to the popular Video Multimethod Assessment Fusion (VMAF) metric for determining optimized bitrate-resolution pairs in the context of Versatile Video Coding (VVC). Our study is rooted in the observation that XPSNR shows a superior correlation with subjective quality scores for VVC-coded Ultra-High Definition (UHD) content compared to VMAF. We predict the average XPSNR of VVC-coded bitstreams using spatiotemporal complexity features of the video and the target encoding configuration and then determine the convex-hull online. On average, the proposed convex-hull using XPSNR (VEXUS) achieves an overall quality…
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Taxonomy
TopicsVideo Coding and Compression Technologies · Advanced Data Compression Techniques · Advanced Image Processing Techniques
