Video quality assessment (QA) continues to be an important area of research due to the overwhelming number of applications where videos are delivered to humans. In particular, the problem of temporal pooling of quality sores has received relatively little attention. We observe a hysteresis effect in the subjective judgment of timevarying video quality based on measured behavior in a subjective study. Based on our analysis of the subjective data, we propose a hysteresis temporal pooling strategy for QA algorithms. Applying this temporal strategy to pool scores from PSNR, SSIM [1] and MOVIE [2] produces markedly improved subjective quality prediction.
Kalpana Seshadrinathan, Alan C. Bovik