AVT-VQDB-UHD-1-HDR: An Open Video Quality Dataset for Quality Assessment of UHD-1 HDR Videos

High dynamic range (HDR) videos offer users a more realistic viewing experience owing to their ability to represent a wider and thus more natural range of brightness. This has resulted in an increase in HDR content streamed on different video streaming platforms. Hence, it becomes important to have a proper understanding of the perceived quality of HDR videos when encoded with modern video codecs such as H.265, AV1, and VVC that are either commonly used or will potentially be used by video streaming providers. With this objective, in this paper, we present a study that used both subjective and instrumental methods to assess the perceived quality of HDR videos. Firstly, a subjective test with 4K/UHD1 HDR videos using the ACR-HR (Absolute Category Rating Hidden Reference) method was conducted. The tests consisted of a total of 195 encoded videos from 5 source videos which all had a framerate of 60 fps. In this test, the 4K/UHD-1 HDR stimuli were encoded at four different resolutions, namely, 720p, 1080p, 1440p, and 2160p using bitrates ranging between 0.5Mbps and 40Mbps. The results of the subjective test have been analyzed to assess the impact of factors such as resolution, bitrate, video codec, and content on the perceived video quality. As automated quality assessment forms an important part of the encoding ecosystem of any video streaming platform to decide the optimal encoding settings, different full reference, bitstream, and hybrid instrumental models have been evaluated for their applicability for HDR video quality prediction. The database of source content, encoded videos, subjective and objective scores is made publicly available with this paper following an open-science approach, accessible at: https://github. com/Telecommunication-Telemedia -Assessment/AVT- VQDB-UHD-1-HDR.