Subjective Assessment of High Dynamic Range Videos Under Different Ambient Conditions

TL;DR

This paper presents the first large-scale subjective study on HDR video quality, examining the effects of distortions and ambient lighting, providing a valuable dataset for future perceptual quality modeling.

Contribution

It introduces the first large-scale publicly available HDR video quality dataset and analyzes the impact of distortions and ambient conditions on perceived quality.

Findings

Compression and aliasing significantly affect HDR video quality.

Ambient lighting conditions influence perceptual quality assessments.

The dataset includes over 20,000 opinion scores from 66 subjects.

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.