Electrical capacitance tomography using an accelerated proximal gradient algorithm.

Image reconstruction in electrical capacitance tomography requires a solution of an ill-posed inverse problem. This paper applies an accelerated proximal gradient (APG) singular value thresholding algorithm, which is originally proposed for the matrix completion problem, to image two-phase flow. Aiming to improve the image quality, a nuclear norm-based regularization technique is adopted to treat the ill-posedness of the inverse problem, and a simple updating technique is used to update the sensitivity matrix. Both typical and complicated distributions (e.g., "sun-rise" and cross-shape), have been examined based on a 16-electrode configuration. The results showed that the APG algorithm with updated sensitivity matrix could produce higher quality images when compared to the algorithm based on the typical sensitivity matrix. Both simulation and experiment results indicate that the algorithm developed has been able to achieve good quality reconstructed images with relativity fast computation speed for the cases tested in this paper.

[1]  W. Smolik,et al.  Performance evaluation of an iterative image reconstruction algorithm with sensitivity matrix updating based on real measurements for electrical capacitance tomography , 2009 .

[2]  Yewang Su,et al.  Investigation of square fluidized beds using capacitance tomography: preliminary results , 2001 .

[3]  Weifu Fang,et al.  A nonlinear image reconstruction algorithm for electrical capacitance tomography , 2004 .

[4]  Artur J. Jaworski,et al.  The design of an electrical capacitance tomography sensor for use with media of high dielectric permittivity , 2000 .

[5]  Hongkai Zhao,et al.  Multilevel bioluminescence tomography based on radiative transfer equation Part 1: l1 regularization. , 2010, Optics express.

[6]  Ø. Isaksen,et al.  A review of reconstruction techniques for capacitance tomography , 1996 .

[7]  Shi Liu,et al.  An image reconstruction algorithm based on the extended Tikhonov regularization method for electrical capacitance tomography , 2009 .

[8]  Jari P. Kaipio,et al.  Tikhonov regularization and prior information in electrical impedance tomography , 1998, IEEE Transactions on Medical Imaging.

[9]  P. Maass,et al.  Tikhonov regularization for electrical impedance tomography on unbounded domains , 2003 .

[10]  Emmanuel J. Candès,et al.  The Power of Convex Relaxation: Near-Optimal Matrix Completion , 2009, IEEE Transactions on Information Theory.

[11]  Zhang Cao,et al.  An image reconstruction algorithm based on total variation with adaptive mesh refinement for ECT , 2007 .

[12]  Manuchehr Soleimani,et al.  Nonlinear image reconstruction for electrical capacitance tomography using experimental data , 2005 .

[13]  Richard A Williams,et al.  Status and applications of microelectrical resistance tomography , 2000 .

[14]  F. Garcia-Nocetti,et al.  Visualisation of gas–oil two-phase flows in pressurised pipes using electrical capacitance tomography , 2005 .

[15]  Wuqiang Yang,et al.  Image reconstruction by nonlinear Landweber iteration for complicated distributions , 2008 .

[16]  Lihui Peng,et al.  Image reconstruction algorithms for electrical capacitance tomography , 2003 .