Helmholtz-type regularization method for permittivity reconstruction using experimental phantom data of ECT


Soleimani, M., Yalavarthy, P. and Dehghani, H., 2010. Helmholtz-type regularization method for permittivity reconstruction using experimental phantom data of ECT. IEEE Transactions on Instrumentation and Measurement, 59 (1), pp. 78-83.

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    Electrical capacitance tomography (ECT) attempts to image the permittivity distribution of an object by measuring the electrical capacitance between sets of electrodes placed around its periphery. Image reconstruction in ECT is a nonlinear ill posed inverse problem, and regularization methods are needed to stabilize this inverse problem. Reconstruction of complex shapes (sharp edges) and absolute permittivity values are more difficult task in ECT and the commonly used regularization methods in Tikhonov minimization are unable to solve these problems. In the standard Tikhonov regularization method, the regularization matrix has a Laplacian type structure, which encourages smoothing reconstruction. A Helmholtz type regularization scheme has been implemented to solve the inverse problem with complicated shape objects and the absolute permittivity values. The Helmholtz type regularization has a wave like property and encourages variations of permittivity. The results from experimental data demonstrate the advantage of the Helmholtz-type regularization for recovering sharp edges over popular Laplacian type regularization in the framework of Tikhonov minimization. Further, this paper presents the examples of the reconstructed absolute value permittivity map in ECT using experimental phantom data.


    Item Type Articles
    CreatorsSoleimani, M., Yalavarthy, P. and Dehghani, H.
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    DepartmentsFaculty of Engineering & Design > Electronic & Electrical Engineering
    Publisher Statementsoleimani-59-1.pdf: Copyright © 2010 IEEE. Reprinted from IEEE Transactions on Instrumentation and Measurement. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bath’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
    ID Code12363


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