A fuzzy image metric with application to fractal coding

Author

Li, Junli ; Chen, Gang ; Chi, Zheru

Author_Institution

Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon, China

Volume

11

Issue

6

fYear

2002

fDate

6/1/2002 12:00:00 AM

Firstpage

636

Lastpage

643

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. A fuzzy image metric (FIM) is defined based on Sugeno´s (1977) 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 the PSNR. Compared to the L²-metric, we demonstrate that a better performance can be achieved in fractal coding by using the proposed FIM

Keywords

correlation methods; data compression; fractals; fuzzy set theory; image coding; image reconstruction; integral equations; noise; video coding; visual perception; PSNR; Sugeno´s fuzzy integral; correlation coefficient; fractal coding; fuzzy image metric; human visual perception; image processing; image reconstruction; image/video compression; objective image quality assessment; peak signal-to-noise ratio; subjective mean opinion score; Degradation; Distortion measurement; Fractals; Humans; Image coding; Image quality; Mathematical model; PSNR; Signal processing; Visual perception;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2002.1014995

Filename

1014995