Xpsnr: A Low-Complexity Extension Of The Perceptually Weighted Peak Signal-To-Noise Ratio For High-Resolution Video Quality Assessment
Christian Helmrich, Mischa Siekmann, Sören Becker, Sebastian Bosse, Detlev Marpe, Thomas Wiegand
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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 algoÂrithmically 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-comÂplexity 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.