Sparse Optimization for Image Reconstruction in Electrical Impedance Tomography

Santhosh Kumar Varanasi1, Chaitanya Manchikatla2, Venkata Goutham Polisetty3, Phanindra Jampana3

  • 1Indian Institute of Technology, Hyderabad.
  • 2Indian Institute of Technology, Hyderabad
  • 3Indian Institute of Technology Hyderabad



Regular Session


10:00 - 11:40 | Wed 24 Apr | Veleiros | WeA1

Inferential Sensing and State Estimation

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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 a sparse solution 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 case studies.

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