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Adaptive Image Enhancement Algorithm Combining Kernel Regression and Local Homogeneity
Joint Authors
Huang, Xing-Fang
Zhang, Jiang-She
Yang, Yu-Qian
Source
Mathematical Problems in Engineering
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-01-09
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
It is known that many image enhancement methods have a tradeoff between noise suppression and edge enhancement.
In this paper, we propose a new technique for image enhancement filtering and explain it in human visual perception theory.
It combines kernel regression and local homogeneity and evaluates the restoration performance of smoothing method.
First, image is filtered in kernel regression.
Then image local homogeneity computation is introduced which offers adaptive selection about further smoothing.
The overall effect of this algorithm is effective about noise reduction and edge enhancement.
Experiment results show that this algorithm has better performance in image edge enhancement, contrast enhancement, and noise suppression.
American Psychological Association (APA)
Yang, Yu-Qian& Zhang, Jiang-She& Huang, Xing-Fang. 2011. Adaptive Image Enhancement Algorithm Combining Kernel Regression and Local Homogeneity. Mathematical Problems in Engineering،Vol. 2010, no. 2010, pp.1-14.
https://search.emarefa.net/detail/BIM-491105
Modern Language Association (MLA)
Yang, Yu-Qian…[et al.]. Adaptive Image Enhancement Algorithm Combining Kernel Regression and Local Homogeneity. Mathematical Problems in Engineering No. 2010 (2010), pp.1-14.
https://search.emarefa.net/detail/BIM-491105
American Medical Association (AMA)
Yang, Yu-Qian& Zhang, Jiang-She& Huang, Xing-Fang. Adaptive Image Enhancement Algorithm Combining Kernel Regression and Local Homogeneity. Mathematical Problems in Engineering. 2011. Vol. 2010, no. 2010, pp.1-14.
https://search.emarefa.net/detail/BIM-491105
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-491105