基于数据融合的ECT图像重建算法

针对固定电极的ECT成像独立测量值较少和因电极位置的影响而导致重建图像失真等问题,提出了基于旋转电极ECT系统模型和数据融合方法来提高重建图像质量。本模型对16电极的ECT模型进行5次旋转,得到的数据采用两种方式进行处理:一是5组数据分别采用线性反投影(LBP)和修正共轭梯度法(MCG)进行重建,再对重建数据进行主分量分析(PCA)的数据融合;二是直接用PCA数据融合再分别进行LBP和MCG图像重建。实验证明:通过增加测量电容数,结合两种数据处理方式可明显提高重构图像质量,降低成像误差。

ECT image reconstruction algorithm based on data fusion

Aiming at the problem that the ECT system with fixed electrodes has the drawbacks of limited measurement data and image distortion caused by the electrode position, a rotating electrode based electrical capacitance tomography (ECT) system model and corresponding data fusion method are proposed to improve the quality of the reconstructed image. This model rotates the 16 electrode ECT model five times, and the resulted measurement data are processed using two methods. In the first method, five sets of the measurement data are reconstructed using Linear Back-Projection (LBP) and Modified Conjugate Gradient (MCG) methods respectively, thereafter the reconstructed data are fused with the principal component analysis (PCA). In the second method, the measurement data are directly fused with PCA and then reconstructed using LBP and MCG respectively. Experiment results show that by increasing the number of measured capacitors, the two data processing methods can obviously improve the quality of reconstructed image and reduce the imaging error.