Assessment and analysis of high dynamic range video quality

In the last decade, high dynamic range (HDR) image and video technology gained a lot of attention, especially within the multimedia community. Recent technological advancements made the acquisition, compression, and reproduction of HDR content easier, and that led to the commercialization of HDR displays and popularization of HDR content. In this context, measuring the quality of HDR content plays a fundamental role in improving the content distribution chain as well as individual parts of it, such as compression and display. However, HDR visual quality assessment presents new challenges with respect to the standard dynamic range (SDR) case. The first challenge is the new conditions introduced by the reproduction of HDR content, e.g. the increase in brightness and contrast. Even though accurate reproduction is not necessary for most of the practical cases, accurate estimation of the emitted luminance is necessary for the objective HDR quality assessment metrics. In order to understand the effects of display rendering on the quality perception, an accurate HDR frame reproduction algorithm was developed, and a subjective experiment was conducted to analyze the impact of different display renderings on subjective and objective HDR quality evaluation. Additionally, in order to understand the impact of color with the increased brightness of the HDR displays, the effects of different color spaces on the HDR video compression performance were also analyzed in another subjective study. Another challenge is to estimate the quality of HDR content objectively, using computers and algorithms. In order to address this challenge, the thesis proceeds with the performance evaluation of full-reference (FR) HDR image quality metrics. HDR images have a larger brightness range and higher contrast values. Since most of the image quality metrics are developed for SDR images, they need to be adapted in order to estimate the quality of HDR images. Different adaptation methods were used for SDR metrics, and they were compared with the existing image quality metrics developed exclusively for HDR images. Moreover, we propose a new method for the evaluation of metric discriminability based ona novel classification approach. Motivated by the need to fuse several different quality databases, in the third part of the thesis, we compare subjective quality scores acquired by using different subjective test methodologies. Subjective quality assessment is regarded as the most effective and reliable way of obtaining “ground-truth” quality scores for the selected stimuli, and the obtained mean opinion scores (MOS) are the values to which generally objective metrics are trained to match. In fact, strong discrepancies can easily be notified across databases when different multimedia quality databases are considered. In order to understand the relationship between the quality values acquired using different methodologies, the relationship between MOS values and pairwise comparisons (PC) scaling results were compared. For this purpose, a series of experiments were conducted using double stimulus impairment scale (DSIS) and pairwise comparisons subjective methodologies. We propose to include cross-content comparisons in the PC experiments in order to improve scaling performance and reduce cross-content variance as well as confidence intervals. The scaled PC scores can also be used for subjective multimedia quality assessment scenarios other than HDR.