A fuzzy metric for image quality assessment

Junli Li, Gang Chen, Zheru Chi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)


Image quality assessment is an important issue addressed in various image processing applications such as image/video compression and image reconstruction. The peak Signal-to-Noise Ratio (PSNR) with the L2-metric is commonly used in objective image quality assessment. However, the measure does not agree very well with the human visual perception in many cases. In this paper, a fuzzy image metric (FIM) is defined based on Sugeno's fuzzy integral. This new objective image metric, which is to some extent a proper evaluation from the viewpoint of the judgement procedure, is closely approximates the subjective Mean Opinion Score (MOS) with a correlation coefficient of about 0.94, as compared to 0.82 obtained using PSNR.
Original languageEnglish
Title of host publicationIEEE International Conference on Fuzzy Systems
Number of pages4
Publication statusPublished - 1 Dec 2001
Event10th IEEE International Conference on Fuzzy Systems - Melbourne, Australia
Duration: 2 Dec 20015 Dec 2001


Conference10th IEEE International Conference on Fuzzy Systems


  • Fuzzy integrals
  • Image metrics
  • Image quality assessment

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics


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