Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17751
Title: A fuzzy metric for image quality assessment
Authors: Li, J
Chen, G
Chi, Z 
Keywords: Correlation methods
Fuzzy set theory
Image coding
Image enhancement
Image reconstruction
Quality control
Issue Date: 2001
Publisher: IEEE
Source: The 10th IEEE International Conference on Fuzzy Systems, 2001, 2-5 December 2001, v. 3, p. 562-565 How to cite?
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 human visual perception in many cases. In this paper, a fuzzy image metric (FIM) is defined based on M. Sugeno's (1974) 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.
URI: http://hdl.handle.net/10397/17751
ISBN: 0-7803-7293-X
DOI: 10.1109/FUZZ.2001.1009016
Appears in Collections:Conference Paper

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