  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.
