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A Display-Independent Quality Assessment for HDR Images.

Authors :
Zhang, Keke
Fang, Ying
Chen, Weiling
Xu, Yiwen
Zhao, Tiesong
Source :
IEEE Signal Processing Letters; 2022, Vol. 29, p464-468, 5p
Publication Year :
2022

Abstract

High Dynamic Range (HDR) images improve visual quality by representing a wide range of luminance in real world. HDR Image Quality Assessment (IQA) is essential in HDR processing technologies. This work focus on the IQA for the HDR applications represented by HDR compression. Towards designing IQA for these tasks, user-end display information should not be considered, given that these tasks only focus on the media intrinsic features. However, most existing HDR metrics are associated with display luminance, hence they can not handle IQA during HDR processing. In this work, we find that it is possible to evaluate HDR image quality without prior knowledge of luminance for display. Based on this, we proposed a low complexity Display-Independent Gradient Magnitude Similarity (DIGMS) metric. Experimental results demonstrate that the proposed DIGMS outperforms the state-of-the-arts in HDR IQA. This work opens up a new perspective for designing IQA algorithms for HDR images. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10709908
Volume :
29
Database :
Complementary Index
Journal :
IEEE Signal Processing Letters
Publication Type :
Academic Journal
Accession number :
155383923
Full Text :
https://doi.org/10.1109/LSP.2022.3141306