title: An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.
abstract: Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.
authors.affiliation: School of Computer Science, Hubei University of Technology, Wuhan 430068, China.
authors.forename: Zhiwei
authors.initials: Z
authors.lastname: Ye
authors.affiliation: School of Computer Science, Hubei University of Technology, Wuhan 430068, China.
authors.forename: Mingwei
authors.initials: M
authors.lastname: Wang
authors.affiliation: School of Educational Information Technology, Huazhong Normal University, Wuhan 430070, China.
authors.forename: Zhengbing
authors.initials: Z
authors.lastname: Hu
authors.affiliation: School of Computer Science, Hubei University of Technology, Wuhan 430068, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted; D008962:Models, Theoretical