Target-background perceptual contrast metric for gray fusion images

Shaoshu Gao, Weiqi Jin, Yanjiang Wang, Xiaodong Zhang

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Perceptual contrast between the target and background is one of the main influencing factors of visible and infrared gray fusion image quality. Existing contrast metrics have not put enough consideration for the human visual system. An simple and effective target-background perceptual contrast metric was proposed combined with the human luminance masking effect based on the form of Weber contrast model. The simulated image and the observer evaluation scores of real scene gray fusion images were used to test the proposed model. Experimental results show that the proposed target-background perceptual contrast metric provides better predictions than five other existing contrast metrics. It is more closely matched to human perceptual evaluation and can efficiently implement the objective evaluation of target-background perceptual contrast for gray fusion images.

Original languageEnglish
Pages (from-to)1660-1665
Number of pages6
JournalHongwai yu Jiguang Gongcheng/Infrared and Laser Engineering
Volume44
Issue number5
Publication statusPublished - 25 May 2015

Keywords

  • Fusion image
  • Human luminance masking effect
  • Objective evaluation
  • Perceptual contrast between the target and background

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