基于Kalman滤波的ECT图像重建算法

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。

ECT image reconstruction algorithm based on Kalman filtering

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.