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Abstract
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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
Submitted: December 20, 2011
Accepted: April 23, 2012
Published: October 15, 2012 |
Abstract:
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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.
Key words: Contrast enhancement, fuzzy c-means clustering algorithm, histogram equalization, , , ,
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Cite this Reference:
Shen-Chuan Tai, Ting-Chou Tsai, Yi-Ying Chang, Wei-Ting Tsai and Kuang-Hui Tang, . Contrast Enhancement through Clustered Histogram Equalization. Research Journal of Applied Sciences, Engineering and Technology, (20): 3965-3968.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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