基于微粒群算法的彩色图像增强研究

Research on Image Enhancement Based on Particle Swarm Optimization

在增强彩色图像问题中,把图像增强看作最优化问题,提出了一种基于微粒群算法的彩色图像自适应增强方法.将在RGB空间表示的降质图像转换到与人类视觉系统特性相适应的HIS颜色空间进行增强,提出了应用于亮度I分量的新的目标函数.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.仿真结果表明所提出的方法在自动拟合灰度的广义变换上有很好的性能,图像增强效果显著.

In this study, a particle swarm optimization （PSO） approach to color image enhancement is proposed, in which image enhancement is formulated as an optimization problem. Here it is assumed that each input--degraded color image is originally represented in the RGB color space, which is converted into the HIS color space for enhancement. The new objective function applied in intensity in the color image enhancement. Using the approach, the optimization parameters in the normalized incomplete Beta function of degraded images can be automatically found out. The simulation results tell that the proposed approach has good performance in generalized exchange of intensity, and the image enhancement effect is prominent.