High Dynamic Range (HDR) and Wide Color Gamut (WCG) screens are able to display images with brighter and darker pixels with more vivid colors than ever. Automatically assessing the quality of these HDR/WCG images is of critical importance to evaluate the performances of image compression schemes. In recent years, full-reference metrics, such as HDR-VDP-2, PU-encoding metrics, have been designed for this purpose. However, none of these metrics consider chromatic artifacts. In this paper, we propose our own full-reference quality metric adapted to HDR and WCG content that is sensitive to chromatic distortions. The proposed metric is based on two existing HDR quality metrics and color image features. A support vector machine regression is used to combine the aforementioned features. Experimental results demonstrate the effectiveness of the proposed metric in the context of image compression.

The inordinate power consumption of contemporary display panels accelerates battery depletion in mobile devices. Existing display-power reduction approaches are suboptimal because they incur additional computations and latency on the mobile device or because they assume a server-client model in which a single entity controls the server and the client. To overcome these limitations, we extract standardized metadata at a server and transmit it to a client along with the video bitstream. This metadata includes quality indicators, associated power controls, and contrast-enhancement information. The metadata guarantees that specified quality levels are achieved while avoiding flicker and minimizing power consumption. Furthermore, the metadata has minimal computational, storage & power overheads and, because it is standardized, the metadata benefits servers and clients in open ecosystems wherein all entities function independently. Our research has been implemented on mobile devices and provides, on average, 32.5 percent power reduction at high quality and up to 84 percent power reduction at acceptable quality. The ISO/IEC Moving Pictures Expert Group has recently standardized our proposed metadata in the Green Metadata Standard.

This paper proposes a brightness control method for retargeting legacy content on High Dynamic Range (HDR) displays. This method is based on a perceptual experiment that evaluates the brightness preference of users. We study the special case of screen content to better understand the effect of image statistics on human preference for brightness. The experiment concluded that brightness preference is highly content dependent. Using the data of the subjective study, we propose a new feature that analyses the source content to appropriately control the brightness of the HDR display. Based on this feature, we propose a brightness control algorithm that adjusts the luminance of display depending on the number of bright pixels in the content.

The vast majority of video content existing today is in Standard Dynamic Range (SDR) format and there is a strong interest in upscaling this content for upcoming High Dynamic Range (HDR) displays. Tone expansion or inverse tone mapping converts SDR content into HDR format using Expansion Operators (EO). In this paper, we show that current EO’s do not perform as well when dealing with content of various lighting style aesthetics. In addition to this, we present a series of perceptual user studies evaluating user preference for lighting style in HDR content. This study shows that tone expansion of stylized content takes the form of gamma correction and we propose a method that adapts the gamma value to the style of the video. We validate our method through a subjective evaluation against state-of-the-art methods. Furthermore, our work has been oriented for 1000 nits HDR displays and we present a framework positioning our method in conformance with existing SDR standards and upcoming HDR TV standards.

Current increasing effort in the television industry towards High Dynamic Range (HDR) imaging has raised the issue of the compression of HDR content. Offering a higher peak luminance and wider color gamut, HDR video introduces new challenges to the state-of-the-art video codecs such as High Efficiency Video Coding (HEVC) or VP9, which have been designed and optimized for the compression of Standard Dynamic Range (SDR) content. This study presents a performance comparison between HEVC and VP9 in the HDR context through both objective and subjective evaluations. The experimental objective results have shown that HEVC offers from 0.6% to 38.2% bit rate savings over VP9 depending on the objective metric which is used. The subjective study demonstrated that, on average, bit rate savings greater than 47.7% can be achieved by HEVC for the same perceived quality as VP9.