A mean-edge structural similarity for image quality assessment

Li Xiong Liu*, Yuan Quan Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Citations (Scopus)

Abstract

Recent studies have found that adoption of structural similarity index (SSIM) was successful in reflecting human visual characteristics better compared with traditional peak signal-to-noise ratio (PSNR) metrics. However, this method shows some weaknesses when evaluating the quality of blurred images and noise images. Good quality results were hardly achieved as they do not match the human visual system (HVS) well. In this paper, we propose an improved image quality assessment algorithm based on mean-edge structural similarity (MESSIM). Edge information is considered sufficiently in image quality assessment. More specifically, the distortion metric of edge structure is assessed. The experimental results have demonstrated better consistency with the subjective perception for a large range of image types.

Original languageEnglish
Title of host publication6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
Pages311-315
Number of pages5
DOIs
Publication statusPublished - 2009
Event6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009 - Tianjin, China
Duration: 14 Aug 200916 Aug 2009

Publication series

Name6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
Volume5

Conference

Conference6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
Country/TerritoryChina
CityTianjin
Period14/08/0916/08/09

Keywords

  • Dual-scale edge structure
  • Image quality assessment
  • JPEG
  • JPEG2000
  • SSIM
  • Subjective perceptual quality

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