SUBJECTIVE ASSESSMENT OF HIGH DYNAMIC RANGE VIDEOS UNDER DIFFERENT AMBIENT CONDITIONS

被引:15
作者
Shang, Zaixi [1 ]
Ebenezer, Joshua P. [1 ]
Bovik, Alan C. [1 ]
Wu, Yongjun [2 ]
Wei, Hai [2 ]
Sethuraman, Sriram [2 ]
机构
[1] Univ Texas Austin, Dept Elect & Comp Engn, Austin, TX 78712 USA
[2] Amazon Prime Video, Seattle, WA USA
来源
2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP | 2022年
基金
美国国家科学基金会;
关键词
High dynamic range (HDR); video quality assessment (VQA); HDR VQA database; ambient illumination;
D O I
10.1109/ICIP46576.2022.9897940
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
High Dynamic Range (HDR) videos can represent a much greater range of brightness and color than Standard Dynamic Range (SDR) videos and are rapidly becoming an industry standard. HDR videos have more challenging capture, transmission, and display requirements than legacy SDR videos. With their greater bit depth, advanced electro-optical transfer functions, and wider color gamuts, comes the need for video quality algorithms that are specifically designed to predict the quality of HDR videos. Towards this end, we present the first publicly released large-scale subjective study of HDR videos. We study the effect of distortions such as compression and aliasing on the quality of HDR videos. We also study the effect of ambient illumination on perceptual quality of HDR videos by conducting the study in both a dark lab environment and a brighter living-room environment. A total of 66 subjects participated in the study and more than 20,000 opinion scores were collected, which makes this the largest in-lab study of HDR video quality ever. We anticipate that the dataset will be a valuable resource for researchers to develop better models of perceptual quality for HDR videos.
引用
收藏
页码:786 / 790
页数:5
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