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Image Reconstruction Method with the Exploitation of the Spatial Correlation for Electrical Capacitance Tomography

Abstract

Electrical capacitance tomography (ECT) is considered to be a competitive measurement method. The imaging objects in ECT measurements are often in a time-varying process, and exploiting the prior information related to the dynamic nature is important for reconstructing high-quality images. Different from existing reconstruction models, in this paper a new model that incorporates the spatial correlation of the pixels by introducing the radial basis function (RBF) method, the dynamic behaviors of a timevarying imaging object, and the ECT measurement information is proposed to formulate the dynamic imaging problem. An objective functional that exploits the spatial correlation of the pixels, the combinational regularizer of the first-order total variation (FOTV) and the second-order total variation (SOTV), the multi-scale regularization, the spatial constraint, and the temporal correlation is proposed to convert the ECT imaging task into an optimization problem. A split Bregman iteration (SBI) method based iteration scheme is developed for solving the proposed objective functional. Numerical simulation results validate the superiority of the proposed reconstruction method on the improvement of the imaging quality.

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Machine–Learning in Optimization of Expensive Black–Box Functions

, Proceedings of the 7th International Conference on Optimization Techniques and Applications (ICOTA 7), Kobe, Japan , pp. 131–132. Poloni, C., Giurgevich, A., Onseti, L. and Pediroda, V. (2000). Hybridization of a multi-objective genetic algorithm, a neural network and a classical optimizer for a complex design problem in fluid dynamics, Computer Methods in Applied Mechanics and Engineering 186 (2–4): 403–420. Powell, M.J.D. (2001). Radial basis function methods for interpolation of functions of many variables

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