摘要
基于遗传算法和非完全Beta函数,介绍了一种自适应的图像对比度增强方法,并将其应用到辐射图像的增强处理中。Tubbs利用归一化的非完全Beta函数(Incomplete Beta Function),来实现几种典型的灰度变换曲线的自动拟合。在实现了该函数的基础上,通过基于遗传算法的自适应搜索确定Beta函数的最佳参数,并对遗传算子做了一定改进,从而确定相应的最佳变换曲线。将该方法应用于集装箱检测图像的对比度增强,通过对实验结果的比较,说明了该方法的优越性。
Based on genetic algorithm and incomplete beta function, we introduce a self-adaptive method for image contrast enhancement and apply this method to radiograph image enhancement. Tubbs integrated the several common nonlinear functions of gray transform as a normalized incomplete beta function for realizing image enhancement, and by taking use of self-adaptive searching algorithm, optimal parameters of incomplete beta function can be determined, thereby determining the corresponding optimal transform curve. In this paper, incomplete beta function and genetic algorithm are applied in contrast enhancement of container cargo inspection image, and the advantages of this method are well illustrated by comparing the experimental results.
出处
《核电子学与探测技术》
CAS
CSCD
北大核心
2007年第1期104-107,共4页
Nuclear Electronics & Detection Technology
