图像增强的自适应免疫算法

介绍了自适应免疫算法的基本原理及实现步骤，并将其应用到图像的增强处理中，在传统的图像管理处理中，针对图像灰度分布的不同情况，需要定义相应的灰度变换函数。Tubbs将图像增强处理中几种常用的非线性变换函数表示成一个归一化的非完全Beta函数，但确定Beta函数参数仍是一个复杂的问题，本文利用自适应免疫算法来确定该变换函数的最佳参数值，通过对自然图像的仿真实验可以看出本文方法的有效性。

Application of immune algorithm to adaptive image enhancement

The principle and steps of immune algorithm are studied, and an adaptive image enhancement method using immune algorithm is proposed. The nonlinear transform of gray level is an efficient way of image enhancement. In classical image enhancement methods, the specific transform function is determined according to the gray level distribution in the processed image. Tubbs proposed a normalized incomplete Beta function to represent the four kinds of nonlinear transform functions most commonly used. But how to adaptively define the coefficients of the Beta function is still a problem. We adopt an adaptive immune algorithm that explicitly searches the optimal or suboptimal coefficients more quickly. Compared with the common image adjustment approach, our method is more efficient and powerful.