基于混合蛙跳优化的条纹管图像自适应增强

摘要

A new kind of adaptive enhancement approach, based on shuffled frog-leaping optimization algorithm and incomplete Beta function, is given to streak tube image of streak tube camera. There is not only the local but also the global information exchange in shuffled frog-leaping algorithm. So the result of exploration is reliable and the speed of consuingency is fast. The adaptive parameters of gray transform fimction are selected by shuffled frog-leaping algorithm,so it could get an optimization curve and enhance the image. Experimental results show that the proposed algorithm is efficient for streak tube image. Compared with traditional enhancement methods, the proposed algorithm can keep the detail of target in the streak image better, and it is superior to traditional enhancement methods in visual quality.%针对条纹管相机荻取的条纹图像,提出一种将混合蛙跳算法和非完全Beta函数结合的自适应增强方法.利用混合蛙跳算法中局部信息交换和全局信息交换的寻优机制,增加寻优稳定性和加快收敛度.通过混合蛙跳优化算法自动搜索最佳灰度变换参数,从而得到一条最佳灰度变换曲线,实现对条纹图像增强处理.实验证明该算法能降低条纹图像中背景对目标的影响,且较好保留了图像中细节部分信息,在视觉上优于传统的增强方法.