A No-Reference Video Quality Assessment Model for Underwater Networks

Abstract

Underwater imagery is increasingly drawing attention from the scientific community, since pictures and videos are invaluable tools in the study of the vast unknown oceanic environment that covers 90% of the planetary biosphere. However, underwater sensor networks must cope with the harsh channel that seawater constitutes. Medium range communication is only possible using acoustic modems that have limited transmission capabilities and peak bitrates of only a few dozens of kilobits per second. These reduced bitrates force heavy compression on videos, yielding much higher levels of distortion than in other video services. Furthermore, underwater video users are ocean researchers, and therefore their quality perception is also different from the generic viewers that typically take part in subjective quality assessment experiments. Computational efficiency is also important since the underwater nodes must run on batteries and their recovery is very expensive. In this paper, we propose a pixel-based no-reference video quality assessment method that addresses the described challenges and achieves good correlations against subjective scores of users of underwater videos. Index Terms-Natural video statistics (NVSs), underwater networks (UWNs), video quality assessment (VQA).