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PSNR-Based Estimation of Subjective Time-Variant Video Quality for Mobiles

With low-rate video services over packet networks, the topic of video quality measuring became even more popular. In the presence of packet loss, the video quality becomes highly time-variant. The subjective quality evaluation is in general correlated with the metrics based on the difference between the degraded sequence and the reference. However, it can diffe r significantly in some cases, thus it provides limited means for the appropriate quality estimation. In this work we focus on the relation between the peak to signal-to-noise ratio (PSNR) and the mean opinion score for the video streams with time variant quality. We study simple human perception rules and use them to correct the PSNR accordingly, to achieve suitable subjective quality estimation, based on objective parameters. We focus on mobile terminals and video applications. Thus, we performed the assessments on mobile terminals using our proposed methodology. The results show considerable improvement of the estimation quality with respect to the PSNR.