Abstract:Aiming at the ill-conditioned inverse problem of electrical capacitance tomography (ECT), a method of introducing convolution sparse coding model into ECT least squares problem as penalty is proposed. The model is solved by pre-trained filter and alternating direction method of multipliersr algorithm (ADMM), and the ECT image reconstruction is completed. The proposed method is simulated and tested experimentally, and compared with LBP, Tikhonov regularization and Landweber iterative algorithm. The results show that the average relative error and correlation coefficient of the reconstructed image obtained by the proposed method are 0.4389 and 0.8968, respectively, which are superior to the other three methods, and the reconstruction quality of central object and multi-object distribution is significantly improved.
Zhao Y, Yue S H, Zhang Y Y, et al. Visual detection of gas-liquid two-phase flow in aeroengine[J]. Journal of Beihang University, 2017,43 (11):2345-2351.
Zhang L F, Zhu Y F. Application of Extreme Learning Machine in Electrical Capacitance Tomography[J]. Electrical Measurement and Instrument, 2020, 57(9):
Ma M, Sun M J. ECT image reconstruction algorithm based on improved linear Bregman algorithm[J]. Acta Metrologica Sinica, 2021,42(7):879-884.
Zhao Y L, Guo B L, Yan Y Y. Research progress and analysis of electrical capacitance tomography[J]. Journal of Instrumentation, 2012,33(8):1909-1920.
Zhang L F, Liu Z L, Tian P. Image reconstruction algorithm of electrical capacitance tomography based on compressive sensing[J]. Journal of Electronics, 2017,45(2):353-358.
Wang Q, Zhang R H, Wang J H, et al. Imaging method of ECT/CT dual-mode fusion system based on compressed sensing[J]. Chinese Journal of Scientific Instrument, 2014,35(6):1338-1346.
[12]
Zeiler M, Krishnan D, Taylor G, et al. Deconvolutional networks[C]//Proceedings of the 2010 IEEE Computer Society Conference on computer vision and pattern recognition. IEEE, 2010:2528-2535.
[13]
Bao P, Xia W J, Yang K, et al.Convolutional Sparse Coding for Compressd Sensing CT Reconstruction[J]. IEEE Transactions on Medical Imaging, 2019,38(11):2607-2619.
Lustig M, Donoho D, Pauly J M. Sparse MRI:the application of compressed sensing for rapid MR imaging[J]. Magnetic Resonance in Medicine, 2007, 58(8):1182-1195.
Li L, Shi N, Kong H H. Sparse angle CT reconstruction algorithm based on total variation and gradient domain convolutional sparse coding [J]. Advances in Laser and Optoelectronics, 2021,58(12):339-348.
14
6-152.
Ma M, Liu Y F, Liu Y N. ECT Image Reconstruction Based on Improved Half-threshold Iterative Algorithm[J].
Ye J M, Wang H G, Yang W Q. Image Reconstruction for Electrical Capacitance Tomography Based on Sparse Representation[J]. IEEE Transactions on Instrumentation and Measurement, 2015,64(1):89-102.
Chen N, Zhang B. Super-resolution reconstruction of remote sensing images with multi-scale semi-coupled convolutional sparse coding [J]. Journal of Computer Aided Design and Graphics, 2022,34(3):382-391.
Zhang L F, Zhang M. An optimization algorithm of electrical capacitance tomography image reconstruction[J]. Acta Metrologica Sinica, 2021,42(9):1155-1159.