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Author:

Zhou, Xiaolin (Zhou, Xiaolin.) | Sun, Guangmin (Sun, Guangmin.) (Scholars:孙光民) | Zhao, Dequn (Zhao, Dequn.) | Wang, Zhimeng (Wang, Zhimeng.) | Gao, Li (Gao, Li.) | Wang, Xiaomeng (Wang, Xiaomeng.) | Jin, Yufeng (Jin, Yufeng.)

Indexed by:

CPCI-S EI Scopus

Abstract:

An improved image enhancement algorithm based on genetic algorithm has been presented and applied for transmission line image processing in this paper, in which fuzziness is served as the optimization method of the image enhancement procedure. Because the complexity and uncertainty of the image itself, fuzzy theory has been used in the image processing. In this process, the parameters of the transformation function are found by the genetic algorithm. Thus, a new kind of image enhancement method is proposed by combining fuzzy theory with the genetic algorithm. Finally, compared with the traditional image enhancement methods, the method presented in this paper is better in performance.

Keyword:

image enhancement image processing genetic algorithm fuzziness

Author Community:

  • [ 1 ] [Zhou, Xiaolin]Beijing Univ Technol, Dept Elect Engn, Beijing 100124, Peoples R China
  • [ 2 ] [Sun, Guangmin]Beijing Univ Technol, Dept Elect Engn, Beijing 100124, Peoples R China
  • [ 3 ] [Zhao, Dequn]Beijing Univ Technol, Dept Elect Engn, Beijing 100124, Peoples R China
  • [ 4 ] [Wang, Zhimeng]Beijing Univ Technol, Dept Elect Engn, Beijing 100124, Peoples R China
  • [ 5 ] [Gao, Li]Beijing Univ Technol, Dept Elect Engn, Beijing 100124, Peoples R China
  • [ 6 ] [Wang, Xiaomeng]Beijing Univ Technol, Dept Elect Engn, Beijing 100124, Peoples R China
  • [ 7 ] [Jin, Yufeng]Beijing Univ Technol, Dept Elect Engn, Beijing 100124, Peoples R China

Reprint Author's Address:

  • [Zhou, Xiaolin]Beijing Univ Technol, Dept Elect Engn, Beijing 100124, Peoples R China

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Source :

2013 NINTH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING (IIH-MSP 2013)

Year: 2013

Page: 223-226

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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