Image Reconstruction Based on 11 Regularization for Electrical Impedance Tomography (EIT)

Electrical impedance tomography (EIT) aims to estimate the electrical properties at the interior of an object from current-voltage measurements on its boundary. The image reconstruction for EIT is an inverse problem, which is both nonlinear and ill-posed. Little noise in the measured data can cause large errors in the estimated conductivity. Image reconstruction using the l(1) regularization allows addressing this difficulty, in comparison to traditional reconstruction using the l(2) regularization or Tikhonov method. In this paper, a sum of absolute values are substituted for the sum of squares used in the Tikhonov regularization to form the l(1) regularization, the solution is obtained by the barrier method. The selection of parameters is also discussed. Both simulation and experimental results of the l(1) regularization method were compared with the l(2) regularization method, indicating the l(1) regularization method can improve the quality of image reconstruction and tolerance a relatively high level of noise in the measured voltages.