video super-resolution quality assessment database (VSR-QAD)-5

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，例如可在高分辨率显示设备上优化老旧低分辨率视频的观看体验。然而，目前尚无专门针对超分辨率视频设计的视觉质量评估（Visual Quality Assessment, VQA）模型，而此类模型对于推动视频SR算法迭代升级与观看质量保障均具有关键意义。为此，我们构建了超分辨率视频质量评估数据库VSR-QAD（Video Super-Resolution Quality Assessment Database），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的倍率进行空间降采样，随后通过10种具有代表性的SR算法将降采样后的视频超分辨率还原至原始分辨率，最终得到2400条超分辨率视频。为获取这批超分辨率视频的主观质量标签，我们开展了心理视觉实验，共有190名受试者参与，总耗时约400小时，完成了绝对评分与相对评分两项实验。在对齐相对评分与绝对评分结果并剔除异常值后，最终有2260条超分辨率视频被标注了平均意见得分（Mean Opinion Score, MOS）。