An Image Reconstruction Algorithm Based on the Regularized Minimax Estimation for Electrical Capacitance Tomography

Electrical capacitance tomography (ECT) is considered as a promising process tomography (PT) technology. Image reconstruction algorithms play an important role in the successful applications of ECT. In this paper, a generalized objective functional, which has been developed using the combinational minimax estimation and a generalized stabilizing functional, is proposed. The Newton algorithm is employed to solve the proposed objective functional. The algorithm is tested by the noise-free capacitance data and the noise-contaminated capacitance data, excellent numerical performances and good results are observed. In the cases considered in this paper, the quality of the reconstructed images is markedly improved, which indicates that the algorithm is successful in solving ECT inverse problem. At the same time, the reconstructed results derived from the noise-contaminated capacitance data indicate that the proposed algorithm is competent to treat with the inaccuracy in the capacitance data. As a result, a promising algorithm is introduced for ECT image reconstruction.