A fuzzy image metric with application to fractal coding

Junli Li, Gang Chen, Zheru Chi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

34 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 judgment 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. Comparing to the L2-metric, we demonstrate that a better performance can be achieved in fractal coding by using the proposed FIM.
Original languageEnglish
Pages (from-to)636-643
Number of pages8
JournalIEEE Transactions on Image Processing
Issue number6
Publication statusPublished - 1 Jun 2002


  • Fractal coding
  • Fuzzy integrals
  • Image metrics
  • Image quality assessment
  • Quadtree partition

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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