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2012 (Vol. 4, Issue: 20)
Article Information:

Contrast Enhancement through Clustered Histogram Equalization

Shen-Chuan Tai, Ting-Chou Tsai, Yi-Ying Chang, Wei-Ting Tsai and Kuang-Hui Tang
Corresponding Author:  Shen-Chuan Tai 

Key words:  Contrast enhancement, fuzzy c-means clustering algorithm, histogram equalization, , , ,
Vol. 4 , (20): 3965-3968
Submitted Accepted Published
December 20, 2011 April 23, 2012 October 15, 2012

This study proposed a contrast enhancement algorithm. Some methods enhance images depending on only the global or the local information, therefore it would cause over-enhancement usually and make the image look unnatural. The proposed method enhances image based on the global and local information. For the global part, we proposed mapping curves to find the new average, maximum and minimum intensity to try to suit the concept of Human Visual System (HVS) for obtaining the better perceptual results. For the local part, we utilized fuzzy c-means clustering algorithm to group image and we can obtain the information of intensity distribution and pixel number from each group. Then we calculate weights according to the information and enhance images by Histogram Equalization (HE) depending on the weights. The experiment results show that our method can enhance the contrast of image steadily and it causes over-enhancement with lower probability than other methods. The whole image not only looks natural but also shows detail texture more clearly after applying our method.
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  Cite this Reference:
Shen-Chuan Tai, Ting-Chou Tsai, Yi-Ying Chang, Wei-Ting Tsai and Kuang-Hui Tang, 2012. Contrast Enhancement through Clustered Histogram Equalization.  Research Journal of Applied Sciences, Engineering and Technology, 4(20): 3965-3968.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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