Quantitative Measurement of Perceptual Attributes and Artifacts for Tone-Mapped HDR Display

Abstract

Measuring electronic display quality, as perceived by human observers, has attracted high attention in current consumer displays. With limited dynamic range of consumer-level standard dynamic range (SDR) displays, high dynamic range (HDR) scenes are often rendered by different tone mapping operators (TMOs). Due to the lack of quantitative measurement and analysis of tone mapping in the existing image quality measurement (IQM) methods, it is of considerable significance to establish new IQM protocols that can differentiate the display quality of SDR electronic devices. We first propose an IQM model to exhibit the essential perceptual attributes and artifacts that are peculiar to tone-mapping. Furthermore, we characterize the overall image quality (OiQ) resulting from linear regression and various machine learning techniques. Finally, the execution of without HDR reference ablation experiments demonstrate the relative contribution of these attribute measurement to the OiQ. The use of IQM protocols helps with well-founded quality measurement between TMOs during tone-mapping processing. Our effort is not only useful to get into the tone-mapping field or when implementing a TMO, but it also sets the stage for quantitative measurement of TMOs. By monitoring these attributes and artifacts after different tone-mapping process, user-driven or optimal display are made possible.