摘要
针对工业CT图像中存在着的前景遮挡,背景噪声干扰和对比度低等问题,提出了一种基于改进鲸鱼优化算法的图像增强方法。首先应用混沌映射对鲸鱼优化算法的种群进行初始化,通过让鲸鱼种群分布的更加广泛来提升全局搜索能力。然后使用莱维飞行对鲸鱼个体的位置进行更新,进一步提高算法的局部搜索能力。最后应用改进的鲸鱼优化方法来寻找CLAHE的最佳参数,实现对图像的自适应最优增强。实验结果显示,相比于几种流行的图像增强算法,本文提出的方法能够更好的对工业CT图像进行增强,能够显著提升图像质量,并保留更多的细节信息。
In order to solve the problems of foreground occlusion,background noise interference,and low contrast in industrial CT images,an image enhancement method based on the improved whale optimization algorithm is proposed.First,tent mapping is used to initialize the population of the whale optimization algorithm,and the global search capability is improved by making the whale population more widely distributed.L vy flight is then used to update the position of individual whales to further improve the local search capability of the algorithm.Finally,the improved whale optimization method is applied to find the best parameters of CLAHE and achieve the adaptive optimal enhancement of the image.Experimental results show that compared with several popular image enhancement algorithms,the method proposed in this article can better enhance industrial CT images,significantly improve image quality,and retain more detailed information.
作者
王紫荆
刘卫星
杨爱民
Wang Zijing;Liu Weixing;Yang Aimin(College of Science,North China University of Science and Technology,Tangshan 063210,China;Comprehensive Test Analysis Center,North China University of Science and Technology,Tangshan 063210,China)
出处
《电子测量技术》
北大核心
2024年第11期160-168,共9页
Electronic Measurement Technology
基金
国家自然科学基金(52074126)
河北省自然科学基金(E2022209110)项目资助。
