Abstract: In this study，a Particle Swarm Optimization（PSO） approach to image enhancement is proposed，in which image enhancement is formulated as an optimization problem.Using the approach，the optimization parameters in the normalized incomplete Beta function of degraded images can be automatically found out.Then accurate illation of the type of original degraded images can be got.In spite of which type of the original images，better result of enhanced image can be obtained.And a new objective function is used during evaluating the performance of algorithms.The efficiency and superiority of PSO algorithms to image enhancement can be showed by the simulation results.

Key words: image enhancement, PSO, incomplete Beta function, objective function

摘要： 提出了一种基于微粒群算法（PSO）的图像增强方法，把图像增强看作最优化问题。使用此方法可以自动地找出降质图像归一化的非完全β函数的最优参数值，对原始图像降质类型进行正确的推理。不论原始图像是哪种降质类型，使用提出的算法都能得到较好的增强。并且在评价算法的性能时，使用了一种新的目标函数。实例仿真证实了PSO在图像增强上的有效性和优越性。

关键词: 图像增强, 微粒群优化算法, 非完全β函数, 目标函数