Paper Info
Title
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 demonstrates the relative contribution of these attribute measurements to 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 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 is made possible.
Year
DOI
Venue
2022
10.1109/TIM.2022.3185322
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Keywords
DocType
Volume
Image color analysis, Brightness, Protocols, Dynamic range, Entropy, Distortion measurement, Machine learning, High dynamic range (HDR), image attributes, image quality measurement (IQM), machine learning, tone mapping operators (TMOs)
Journal
71
ISSN
Citations 
PageRank 
0018-9456
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Mingxing Jiang101.01
Liquan Shen2122686.47
Min Hu33112.64
Ping An454568.73
Yu Gu512810.99
Fuji Ren6803135.33