No-reference image contrast assessment based on just-noticeable-difference

Minsub Kim, Ki Sun Song, Moon Gi Kang

Research output: Contribution to journalConference articlepeer-review

7 Citations (Scopus)


Image quality assessment (IQA) has been important issue in image processing. While using subjective quality assessment for image processing algorithms is suitable, it is hard to get subjective quality because of time and money. A lot of objective quality assessment algorithms are used widely as a substitution. Objective quality assessment divided into three types based on existence of reference image: full-reference, reduced-reference, and no-reference IQA. No-reference IQA is more difficult than full-reference IQA because it does not have any reference image. In this paper, we propose a novel no-reference IQA algorithm to measures contrast of image. The proposed algorithm is based on just-noticeable-difference which utilizes the human visual system (HVS). Experimental results show the proposed method performs better than conventional no-reference IQAs.

Original languageEnglish
Pages (from-to)26-29
Number of pages4
JournalIS and T International Symposium on Electronic Imaging Science and Technology
Publication statusPublished - 2017
EventImage Quality and System Performance XIV, IQSP 2017 - Burlingame, United States
Duration: 2017 Jan 292017 Feb 2

Bibliographical note

Publisher Copyright:
© 2017, Society for Imaging Science and Technology.

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics


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