DocumentCode :
679570
Title :
An image reconstruction algorithm for ECT using enhanced model and sparsity regularization
Author :
Yunjie Yang ; Lihui Peng
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
fYear :
2013
fDate :
22-23 Oct. 2013
Firstpage :
35
Lastpage :
39
Abstract :
An image reconstruction algorithm for electrical capacitance tomography (ECT) using enhanced linear model and sparsity regularization (EMSR) is proposed in this paper. Compared to the traditional ECT linear model, the enhanced linear model takes the nonlinear effect of different capacitance groups and the sensitivity error into account. In addition, the sparsity of permittivity distributions under wavelet basis is investigated and utilized as the regularization term. The proposed algorithm using enhanced model and sparsity regularization is noted as EMSR and the performance is verified by using simulation data and experiment data. Both the simulation and experiment results indicate the potentiality of this method.
Keywords :
Gaussian distribution; image reconstruction; tomography; ECT; EMSR; electrical capacitance tomography; enhanced linear model; image reconstruction; sensitivity error; sparsity regularization; Bars; Capacitance; Electrical capacitance tomography; Image reconstruction; Permittivity; Phantoms; Sensitivity; electrical capacitance tomography; enhanced linear model; image reconstruction; wavelet basis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Imaging Systems and Techniques (IST), 2013 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-5790-6
Type :
conf
DOI :
10.1109/IST.2013.6729658
Filename :
6729658
Link To Document :
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