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Electrical Engineering and Systems Science > Image and Video Processing

arXiv:2209.10005 (eess)
[Submitted on 20 Sep 2022]

Title:Subjective Assessment of High Dynamic Range Videos Under Different Ambient Conditions

Authors:Zaixi Shang, Joshua P. Ebenezer, Alan C. Bovik, Yongjun Wu, Hai Wei, Sriram Sethuraman
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Abstract: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.
Subjects: Image and Video Processing (eess.IV); Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2209.10005 [eess.IV]
  (or arXiv:2209.10005v1 [eess.IV] for this version)
  https://doi.org/10.48550/arXiv.2209.10005

Submission history

From: Zaixi Shang [view email]
[v1] Tue, 20 Sep 2022 21:25:50 UTC (2,710 KB)
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