基于Kalman滤波的ECT图像重建算法  

ECT image reconstruction algorithm based on Kalman filtering

作　　者：李佳[1] 张立峰[1] 田沛[1] 

机构地区：[1]华北电力大学自动化系,河北保定071003

出　　处：《传感器与微系统》2015年第8期128-130,共3页Transducer and Microsystem Technologies

基　　金：国家自然科学基金资助项目(51306058);中央高校基本科研业务费专项资金资助项目(2014MS142)

摘　　要：由于测量环境等因素的影响,实测数据往往带有噪声。为此,应用Kalman滤波算法进行电容层析成像(ECT)系统图像重建,在归一化电容值中加入不同程度的噪声信号,利用噪声的统计特性进行测量值滤波,最终得到图像灰度值。在三种流型下与Landweber迭代算法进行了仿真比较,并在ECT实验装置上进行了静态实验。仿真与实验结果表明:Kalman滤波去噪效果优于Landweber迭代算法。Due to influence of environmental factors,measurement datas often contain noise. For this,Kalman filtering algorithm is applied in electrical capacitance tomography（ ECT）to reconstruct image,add noise signals of different degree in the normalized capacitance value,measured value filtering is carried out using statistical properties of noise,and obtain image gray value finally. Three flow patterns are selected for simulation experiments and compared with Landweber algorithm,and static experiment is carried out using ECT device. Simulation and experimental results show that the denoising effect of Kalman filtering is better than Landweber algorithm.

关 键 词：电容层析成像 图像重建 KALMAN滤波 

分 类 号：TP317.4[自动化与计算机技术—计算机软件与理论]