一种使用混合智能优化算法的图像增强方法

Image Enhancement Using Hybrid Intelligent Optimization

对比度增强在图像处理系统中常用来提高降质图像质量或增强图像细节。从优化问题的角度来处理图像增强,提出了用混合智能算法,结合细菌觅食优化算法和粒子群优化算法的优点,对图像增强算子的参数进行优化,使图像质量达到最佳。使用的增强算子取决于源图像的局部灰度信息和全局统计信息,采用的适应度函数是基于图像的边缘信息和熵信息。仿真和实验结果表明该方法不仅能实现图像对比度增强还能有效提高目标图像的细节,并有效抑制噪声。

Contrast enhancement is in common use to improve image quality or strengthen image details in degraded images because of its important role in image processing system.In this paper,from the point of optimization problem,a kind of hybrid intelligent algorithm that combined the advantage of bacteria foraging optimization algorithm and particle swarm optimization algorithm is proposed to deal with image enhancement,which could help to achieve the best image quality by optimizing parameters of image enhancement operator.The enhancement operator dependes on local gray level information and global statistics information of the source image,the fitness function based on edge information and entropy information of the image.The results of simulation and experiment show that after the application of this method not only contrast enhancement and details of target image are effectively improved,but also noise of image is effectively suppressed.