Image Fuzzy Enhancement Based on Self-Adaptive Bee Colony Algorithm
Abstract: 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 selfadaptive 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.
Author: Meng Le
Journal Code: jptkomputergg140122
