Automatic image enhancement by artificial bee colony algorithm | Zendy

Adiljan Yimit | Zendy; Yoshihiro Hagihara | Zendy; Tasuku MIYOSHI | Zendy; Yukari Hagihara | Zendy

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Automatic image enhancement by artificial bee colony algorithm

Author(s) -

Adiljan Yimit,

Yoshihiro Hagihara,

Tasuku MIYOSHI,

Yukari Hagihara

Publication year - 2013

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.2010802

Subject(s) - artificial bee colony algorithm , particle swarm optimization , computer science , artificial intelligence , entropy (arrow of time) , fitness function , genetic algorithm , image (mathematics) , process (computing) , image enhancement , computer vision , algorithm , pattern recognition (psychology) , machine learning , physics , quantum mechanics , operating system

editor: Zeng ZhuWith regard to the improvement of image quality, image enhancement is an important process to assist human with better perception. This paper presents an automatic image enhancement method based on Artificial Bee Colony (ABC) algorithm. In this method, ABC algorithm is applied to find the optimum parameters of a transformation function, which is used in the enhancement by utilizing the local and global information of the image. In order to solve the optimization problem by ABC algorithm, an objective criterion in terms of the entropy and edge information is introduced to measure the image quality to make the enhancement as an automatic process. Several images are utilized in experiments to make a comparison with other enhancement methods, which are genetic algorithm-based and particle swarm optimization algorithm-based image enhancement methods

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