A fuzzy metric for image quality assessment

Author

Li, Junli ; Chen, Gang ; Chi, Zheru

Author_Institution

Inst. of Sci., Zhejiang Univ., Hangzhou, China

Volume

2

fYear

2001

Firstpage

562

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.

Keywords

correlation methods; fuzzy set theory; image coding; image enhancement; image reconstruction; quality control; L²-metric; Sugeno fuzzy integral; correlation coefficient; fuzzy image metric; human visual perception; image compression; image processing applications; image quality assessment; image reconstruction; judgement procedure; mean opinion score; objective metric; peak signal-to-noise ratio; subjective metric; video compression; Additive noise; Distortion measurement; Frequency measurement; Humans; Image quality; Mathematical model; Noise measurement; PSNR; Visual perception; Visual system;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2001. The 10th IEEE International Conference on

Print_ISBN

0-7803-7293-X

Type

conf

DOI

10.1109/FUZZ.2001.1009016

Filename

1009016