• 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