Image Fuzzy Enhancement Based on Self-Adaptive Bee Colony Algorithm
Image Fuzzy Enhancement Based on Self-Adaptive Bee Colony Algorithm
In the image acquisition or transmission, the image may be damaged and distorted due to various reasons; therefore, in order to satisfy people’s visual effects, these images with degrading quality must be processed to meet practical needs. Integrating artificial bee colony algorithm and fuzzy set, this paper introduces fuzzy entropy into the self-adaptive fuzzy enhancement of image so as to realize the self-adaptive parameter selection. In the meanwhile, based on the exponential properties of information increase, it proposes a new definition of fuzzy entropy and uses artificial bee colony algorithm to realize the self-adaptive contrast enhancement under the maximum entropy criterion. The experimental result shows that the method proposed in this paper can increase the dynamic range compression of the image, enhance the visual effects of the image, enhance the image details, have some color fidelity capacity and effectively overcome the deficiencies of traditional image enhancement methods.
Dokumentinformationen
Image Fuzzy Enhancement Based on Self-Adaptive Bee Colony Algorithm
2014-12-01
doi:10.12928/telkomnika.v12i4.534
TELKOMNIKA (Telecommunication Computing Electronics and Control); Vol 12, No 4: December 2014; 875-882 ; 2302-9293 ; 1693-6930 ; 10.12928/telkomnika.v12i4
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
| DDC: | 629 |
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