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Xpsnr: A Low-Complexity Extension of the Perceptually Weighted Peak Signal-To-Noise Ratio for High-Resolution Video Quality Assessment

: Helmrich, C.R.; Siekmann, M.; Becker, S.; Bosse, S.; Marpe, D.; Wiegand, T.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society; IEEE Signal Processing Society:
IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020. Proceedings : May 4-8, 2020, Barcelona, Spain
Piscataway, NJ: IEEE, 2020
ISBN: 978-1-5090-6631-5
ISBN: 978-1-5090-6632-2
International Conference on Acoustics, Speech and Signal Processing (ICASSP) <45, 2020, Barcelona>
Fraunhofer HHI ()

The objective PSNR metric is known to correlate quite poorly with subjective assessments of video coding quality. Thus, a number of alternative VQA measures such as (MS-)SSIM and VMAF have been proposed. These, however, are often algorithmically complex and difficult to use for visually motivated encoder optimization tasks, especially subjectively optimized bit allocation. In this paper we show that, by way of low-complexity enhancements of our previous work on a perceptually weighted PSNR (WPSNR) metric, addressing shortcomings with video and ultra high-definition content, the prediction of human judgments of video coding quality by the WPSNR can be improved. In fact, the resulting XPSNR seems to match the performance of the aforementioned state-of-the-art methods.