Image reconstruction method of electromagnetic tomography based on finite rate of innovation

Abstract

In order to improve the image reconstruction quality of electromagnetic tomography (EMT), a new EMT image reconstruction method based on finite rate of innovation (FRI) is put forward in this paper. The FRI sampling process is used to extract the feature information and combined a new measurement equation. Firstly, the conductivity distribution of the target object inside pipeline is modeled as an one-dimensional FRI signal, and then be sampled with polynomial reproducing kernel in FRI sampling framework. Then, more measurements are obtained from these samples, which generate a new mathematical model for EMT image reconstruction problem. Finally, the original image signal is recovered by solving a L0 norm optimization problem with matching pursuit (OMP) algorithm. Experiment result shows that the image error and correlation coefficient of reconstructed images by the proposed method are much better than corresponding indicators obtained by Linear back-projection (LBP), Landweber and Total variation (TV) regularization algorithm. So it is a kind of EMT image reconstruction method with high efficiency and accuracy, which also provides a new method and means for EMT research.