Image reconstruction method of electrical capacitance tomography based on compressed sensing principle

Abstract

To improve the image reconstruction quality of electrical capacitance tomography (ECT), a new ECT image reconstruction method based on compressed sensing principle is proposed. The capacitances’ collection of the ECT system is regarded as linear measurement of compressed sensing; the measurement matrix is designed by randomly realigning the row vectors of a new sensitivity matrix, which is reconstructed by zero vectors’ expansion of the original sensitivity matrix, and the capacitance vectors expanded in the same way are regarded as measurement signals of compressed sensing. The original signal, i.e. permittivity distribution of some object inside a pipeline, is recovered by orthogonal matching pursuit algorithm. Finally, the simulation experiments are performed. The experimental results have shown that the average image reconstruction error and correlation coefficient obtained by this method are better than the corresponding indicators obtained by linear back-projection algorithm, Landweber iterative algorithm and total variation regularization algorithm. Therefore, it is a kind of ECT image reconstruction method with high accuracy, which also provides a new method and means for ECT research.