Sparse optimization for image reconstruction in Electrical Impedance Tomography

Electrical Impedance Tomography (EIT) can be used to obtain phase boundaries and gas holdups in multiphase flows. The main challenge in image reconstruction using EIT is the low spatial resolution. In this paper, a reconstruction algorithm using sparse optimization techniques is presented. For multiphase flows, gradients in the conductivity vector are sparse. Therefore, the reconstruction problem is formulated as identification of this sparse vector given the current-voltage measurements. A new iterative algorithm is proposed to estimate the conductivity values. The accuracy of the proposed method is demonstrated with the help of several examples and comparison with an existing technique. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.