An image reconstruction algorithm for electrical capacitance tomography based on robust principle component analysis

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Abstract

Electrical capacitance tomography (ECT) attempts to reconstruct the permittivity distribution of the cross-section of measurement objects from the capacitance measurement data, in which reconstruction algorithms play a crucial role in real applications. Based on the robust principal component analysis (RPCA) method, a dynamic reconstruction model that utilizes the multiple measurement vectors is presented in this paper, in which the evolution process of a dynamic object is considered as a sequence of images with different temporal sparse deviations from a common background. An objective functional that simultaneously considers the temporal constraint and the spatial constraint is proposed, where the images are reconstructed by a batching pattern. An iteration scheme that integrates the advantages of the alternating direction iteration optimization (ADIO) method and the forward-backward splitting (FBS) technique is developed for solving the proposed objective functional. Numerical simulations are implemented to validate the feasibility of the proposed algorithm. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

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Lei, J., Liu, S., Wang, X., & Liu, Q. (2013). An image reconstruction algorithm for electrical capacitance tomography based on robust principle component analysis. Sensors (Switzerland), 13(2), 2076–2092. https://doi.org/10.3390/s130202076

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