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.

中文翻译：

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水下网络无参考视频质量评估模型

水下图像越来越受到科学界的关注，因为图片和视频是研究覆盖 90% 行星生物圈的广阔未知海洋环境的宝贵工具。然而，水下传感器网络必须应对海水构成的恶劣通道。中距离通信只能使用传输能力有限且峰值比特率仅为每秒几十千比特的声学调制解调器。这些降低的比特率强制对视频进行大量压缩，从而产生比其他视频服务更高的失真水平。此外，水下视频用户是海洋研究人员，因此他们的质量感知也不同于通常参与主观质量评估实验的一般观众。计算效率也很重要，因为水下节点必须依靠电池运行，而且它们的恢复成本非常高。在本文中，我们提出了一种基于像素的无参考视频质量评估方法，该方法解决了所描述的挑战，并与水下视频用户的主观评分实现了良好的相关性。