ECT Image Reconstruction Algorithm Based on Generalized Regularization

Authors

Ma Min, College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;
Guo Qi, College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;
Chaoqi Yan, College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;

Abstract

Abstract: Aiming at the numerical instability caused by the singular value decomposition algorithm and the over-smooth caused by the Tiknonov regularization in the image reconstruction of electrical capacitance tomography (ECT) system, a more generalized regularization algorithm was proposed. The penalty phase of the regularized objective function was modified by the positive definite matrix so that it could reconstruct the image with non smooth information, In the process of solving the objective function, the diagonal weight matrix was introduced, and the data items based on l₂-norm were improved. By comparing the image quality, the relative error of the image and the relative coefficient of the image, the three algorithms were evaluated. Resultsshow that the generalized regularization algorithm compared to Tiknonov regularization algorithm and singular value decomposition algorithm, can distinguish the substance field in different medium effectively and obtain high quality reconstruction images while avoiding over-smooth.

Recommended Citation

Min, Ma; Qi, Guo; and Yan, Chaoqi (2020) "ECT Image Reconstruction Algorithm Based on Generalized Regularization," Journal of System Simulation: Vol. 29: Iss. 8, Article 28.
DOI: 10.16182/j.issn1004731x.joss.201708028
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss8/28

First Page

1851

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201708028

Last Page

1858

CLC

TN911.73

Recommended Citation

Ma Min, Guo Qi, Yan Chaoqi. ECT Image Reconstruction Algorithm Based on Generalized Regularization[J]. Journal of System Simulation, 2017, 29(8): 1851-1858.

DOI

10.16182/j.issn1004731x.joss.201708028