video super-resolution quality assessment database (VSR-QAD)-6

Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment. Our VSR-QAD consists of 120 high quality high resolution reference videos. These videos were first spatially down-scaled by a factor of x2, x4, and x8, and then super-resolved back to their original resolutions by 10 representative SR algorithms to obtain 2,400 SR videos. Psychovisual experiments were carried out to acquire subjective quality labels for these SR videos. 190 subjects spending a total of approximately 400 hours to carry out both absolute rating and relative rating experiments. After aligning these relative and absolute scores and removing outliers, 2,260 SR videos are labeled with mean opinion scores (MOSs).视频超分辨率（Video Super-Resolution，SR）具有重要的现实应用价值，例如可提升老旧低分辨率视频在高分辨率显示设备上的观看体验。然而，目前尚无专门用于评估超分辨率视频的视觉质量评估（Visual Quality Assessment，VQA）模型，而这类模型对于推动视频超分辨率算法的发展以及保障观看画质均至关重要。为此，我们构建了超分辨率视频质量评估数据库（VSR-QAD），用于开展超分辨率视频质量评估相关研究。该数据库包含120条高质量高分辨率参考视频。我们首先将这些参考视频分别以x2、x4、x8的倍率进行空间下采样，随后通过10种代表性超分辨率算法将其超分辨率重建至原始分辨率，由此得到2400条超分辨率视频。我们开展了心理视觉实验，以获取这些超分辨率视频的主观质量标签。共有190名受试者参与实验，总耗时约400小时，完成了绝对评分与相对评分两类实验。在对相对评分与绝对评分进行对齐并剔除异常值后，最终为2260条超分辨率视频标注了平均主观得分（Mean Opinion Score，MOS）。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于评估超分辨率视频质量的数据库，包含120个参考视频，通过下采样和10种超分辨率算法生成2,400个处理视频，并基于主观实验为2,260个视频提供了平均意见分数（MOS）。数据集专注于信号和图像处理领域，旨在支持超分辨率算法开发和视觉质量保证研究。