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Contrast enhancement using adaptively modified histogram equalization

Authors
Kim, Hyoung-JoonLee, Jong-MyungLee, Jin-AeonOh, Sang-GeunKim, Whoi Yul
Issue Date
Dec-2006
Publisher
Springer Verlag
Keywords
Contrast enhancement; Histogram equalization; Image enhancement
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.4319 LNCS, pp.1150 - 1158
Indexed
SCOPUS
Journal Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
4319 LNCS
Start Page
1150
End Page
1158
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/180630
DOI
10.1007/11949534_116
ISSN
0302-9743
Abstract
A new contrast enhancement method called adaptively modified histogram equalization (AMHE) is proposed as an extension of typical histogram equalization. To prevent any significant change of gray levels between the original image and the histogram equalized image, the AMHE scales the magnitudes of the probability density function of the original image before equalization. The scale factor is determined adaptively based on the mean brightness of the original image. The experimental results indicate that the proposed method not only enhances contrast effectively, but also keeps the tone of the original image.
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