一种新的电容层析成像边界灰度补偿算法  

A New Gray Boundary Compensation Algorithm for Electrical Capacitance Tomography System

作　　者：陈宇[1] 李红波[1] 黄仲洋[1] 

机构地区：[1]东北林业大学信息与计算机工程学院,黑龙江哈尔滨150040

出　　处：《哈尔滨理工大学学报》2016年第2期8-12,19,共6页Journal of Harbin University of Science and Technology

基　　金：中央高校基本科研业务费专项资金(DL12CB02);黑龙江省教育厅科学技术研究项目(12513016);黑龙江省博士后基金;黑龙江省自然科学基金(F201347);哈尔滨市科技创新人才专项资金(2013RFQXJ100)

摘　　要：由于电容层析成像(ECT)图像重建典型病态问题的不稳定性,在传统的电容层析成像算法的基础上提出了一种基于遗传蚁群算法(GAAC)的边界灰度补偿算法.在阐述了电容层析成像基本原理的基础上,通过推导多项式加速算法的数学模型,进行该算法的ECT图像重建.但由于传统的电容层析成像算法在图像边界上表现出极大的误差和不稳定性,所以提出了GAAC的边界灰度补偿算法.仿真和数值实验的结果显示,GAAC的边界灰度补偿算法是一种有效的电容层析成像方法,在ECT图像重建算法的领域提出了一个新的尝试.To solve the instability of electrical capacitance tomography technology,a typical problem,based on Genetic Ant Colony Algorithm,an image reconstruction algorithm for electrical capacitance tomography is presented. On analysis of the basic principles of the ECT system,deduced mathematical model of polynomial acceleration algorithm to solve the problem of electrical capacitance tomography,and adopted it to reconstruct ECT image. However,the traditional electrical capacitance tomography algorithm in image edge showed great error and instability,so this paper proposes an genetic ant colony algorithm to compensate for the gray border around the image. Experimental results and simulation data indicate that this new algorithm presents a feasible and effective way to research on image reconstruction algorithm for Electrical Capacitance Tomography System.

关 键 词：电容层析成像 图像重建 蚁群算法 遗传算法 补偿算法 

分 类 号：TP319[自动化与计算机技术—计算机软件与理论]