基于混沌粒子群算法的医学图像增强

经典的模糊增强算法在应用于医学图像时,由于在采集或者传输图像时,外部的干扰较多,图像较大几率会不够清晰,该算法的的控制参数是由手动调整控制的,效率和增强效果较差,无法达到最优。由于粒子群算法存在调整参数少,全局寻优的能力,本文将混沌粒子群算法和模糊增强算法结合,运用混沌粒子群算法对模糊增强的增强参数进行优化,仿真实验证实,对于优化后的混沌粒子群算法,可以使模糊的医学图像的清晰率提高95%以上,同时可以突出某些特征,有效地改善了医学图像的视觉效果。

Medical Image Enhancement Based on Chaotic Particle Swarm Optimization Algorithm

Medical images in the process of collection and transmission,blurred susceptible to noise interference,control parameters of traditional fuzzy enhancement algorithm is controlled by manual adjustment,efficiency and enhancement effect is poorer,unable to achieve the optimal.Due to low particle swarm algorithm to adjust parameters,the ability of global optimization,this paper combines chaotic particle swarm optimization(pso)algorithm and fuzzy enhancement algorithm,chaos particle swarm optimization(pso)algorithm is used to enhance the parameters of the fuzzy enhancement is optimized,the simulation results show that chaos particle swarm optimization(pso)algorithm optimization can effectively will become clear in the medical image,can highlight certain characteristics at the same time,effectively improve the visual effect of medical image.