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A fuzzy image metric with application to fractal coding

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3 Author(s)
Junli Li ; Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon, China ; Gang Chen ; Zheru Chi

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

Published in:

IEEE Transactions on Image Processing  (Volume:11 ,  Issue: 6 )