An Image Fuzzy Enhancement Adopting Linear Membership Function

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S.K.Pal's fuzzy set theory has been used to deal with the degraded image, wherein the image edges are uncertain and inaccurate. But Pals algorithm losses low grey level information of the original image and the grayscales of the image can not be extended. A fuzzy image enhancement based on linear membership function is proposed through the analysis of classical Pal's fuzzy enhancement. This algorithm avoids the lost of low grades information of the image as well as increases the image's whole grey scales. It is very suited for low grades, low contrast images such as X-ray images. As a result of the linear transformation comparing with Pal's non-linear scheme, the image processing speed is also improved. Experiment results show that the proposed method outperforms traditional Pal's in terms of contrast stretching effect and speed.

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2213-2216

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March 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Pal S K, King R A. Image enhancement using smoothing with fuzzy sets [J]. IEEE trans. syst. M an, cybern. , 1981 SMC - 11. (7):494-501.

DOI: 10.1109/tsmc.1981.4308726

Google Scholar

[2] Scott T. Acton. On fuzzy nonlinear regression for image enhancement. Journal of Mathematical Imaging and Vision. Vol 8, No. 3, pp.239-253, (1998).

Google Scholar

[3] H. D. Cheng, and Y. H. Chen, and Y. Sun. A novel fuzzy entropy approach to image enhancement and thresholding. Signal Processing. Vol 75, No. 3, pp.277-301, (1999).

DOI: 10.1016/s0165-1684(98)00239-4

Google Scholar

[4] Peng Dong-liang, Xue An-ke. Degraded Image Enhancement with Applications in RobotVision. IEEE International Conference on Systems, Man and Cybernetics, Vol. 2. p.1837 – 1842, (2005).

DOI: 10.1109/icsmc.2005.1571414

Google Scholar

[5] N, Ostu. A Threshold Selection Method from Gray-Level Histograms[J]. IEEE trans. Syst., Man, cybern, 1979 SMC-9. (7): 62-66.

DOI: 10.1109/tsmc.1979.4310076

Google Scholar