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author:

Zhang, Keke (Zhang, Keke.) [1] | Fang, Ying (Fang, Ying.) [2] | Chen, Weiling (Chen, Weiling.) [3] | Xu, Yiwen (Xu, Yiwen.) [4] | Zhao, Tiesong (Zhao, Tiesong.) [5]

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EI

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. 1070-9908 © 2022 IEEE.

Keyword:

Computer vision Image enhancement Image quality Luminance

Community:

  • [ 1 ] [Zhang, Keke]Fuzhou University, Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou; 350108, China
  • [ 2 ] [Fang, Ying]Fuzhou University, Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou; 350108, China
  • [ 3 ] [Chen, Weiling]Fuzhou University, Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou; 350108, China
  • [ 4 ] [Xu, Yiwen]Fuzhou University, Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou; 350108, China
  • [ 5 ] [Zhao, Tiesong]Fuzhou University, Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fuzhou; 350108, China
  • [ 6 ] [Zhao, Tiesong]Peng Cheng Laboratory, Shenzhen; 518055, China

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Source :

IEEE Signal Processing Letters

ISSN: 1070-9908

Year: 2022

Volume: 29

Page: 464-468

3 . 9

JCR@2022

3 . 2 0 0

JCR@2023

ESI HC Threshold:66

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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