A fuzzy image metric with application to fractal coding

Junli Li; Gang Chen; Zheru Chi

doi:10.1109/TIP.2002.1014995

A fuzzy image metric with application to fractal coding

Junli Li, Gang Chen, Zheru Chi

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

34 Citations (Scopus)

Abstract

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 language	English
Pages (from-to)	636-643
Number of pages	8
Journal	IEEE Transactions on Image Processing
Volume	11
Issue number	6
DOIs	https://doi.org/10.1109/TIP.2002.1014995
Publication status	Published - 1 Jun 2002

Keywords

Fractal coding
Fuzzy integrals
Image metrics
Image quality assessment
Quadtree partition

ASJC Scopus subject areas

Software
Computer Graphics and Computer-Aided Design

More information

10.1109/TIP.2002.1014995

Cite this

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A fuzzy image metric with application to fractal coding

Abstract

Keywords

ASJC Scopus subject areas

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