Efficient contrast enhancement of images using hybrid ant colony optimisation, genetic algorithm, and simulated annealing

被引:51
作者
Hoseini, Pourya [1 ]
Shayesteh, Mahrokh G. [1 ,2 ]
机构
[1] Urmia Univ, Dept Elect Engn, Orumiyeh, Iran
[2] Sharif Univ Technol, Dept Elect Engn, ACRI, Wireless Res Lab, Tehran, Iran
关键词
Image processing; Contrast enhancement; Ant Colony Optimisation (ACO); Genetic Algorithm (GA); Simulated Annealing (SA); Hybrid metaheuristics; ACO; EDGE;
D O I
10.1016/j.dsp.2012.12.011
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we propose a hybrid algorithm including Genetic Algorithm (GA), Ant Colony Optimisation (ACO), and Simulated Annealing (SA) metaheuristics for increasing the contrast of images. In this way, contrast enhancement is obtained by global transformation of the input intensities. Ant colony optimisation is used to generate the transfer functions which map the input intensities to the output intensities. Simulated annealing as a local search method is utilised to modify the transfer functions generated by ant colony optimisation. And genetic algorithm has the responsibility of evolutionary process of ants' characteristics. The employed fitness function operates automatically and tends to provide a balance between contrast and naturalness of images. The results indicate that the new method achieves images with higher contrast than the previously presented methods from the subjective and objective viewpoints. Further, the proposed algorithm preserves the natural look of input images. (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:879 / 893
页数:15
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