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Volume 14, Issue 1
Second-Order Total Variation and Primal-Dual Algorithm for CT Image Reconstruction

S.-S. Luo, Q. Lv, H.-S. Chen & J.-P. Song

Int. J. Numer. Anal. Mod., 14 (2017), pp. 76-87.

Published online: 2016-01

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  • Abstract

In this paper, we proposed a regularization model based on second-order total variation for CT image reconstruction, which could eliminate the 'staircase' caused by total variation (TV) minimization. Moreover, some properties of second-order total variation were investigated, and a primal-dual algorithm for the proposed model was presented. Some numerical experiments for various projection data were conducted to demonstrate the efficiency of the proposed model and algorithm.

  • Keywords

CT image reconstruction, regularization method, second-order total variation, primal-dual algorithm.

  • AMS Subject Headings

92C55, 15A29

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{IJNAM-14-76, author = {S.-S. Luo, Q. Lv, H.-S. Chen and J.-P. Song}, title = {Second-Order Total Variation and Primal-Dual Algorithm for CT Image Reconstruction}, journal = {International Journal of Numerical Analysis and Modeling}, year = {2016}, volume = {14}, number = {1}, pages = {76--87}, abstract = {

In this paper, we proposed a regularization model based on second-order total variation for CT image reconstruction, which could eliminate the 'staircase' caused by total variation (TV) minimization. Moreover, some properties of second-order total variation were investigated, and a primal-dual algorithm for the proposed model was presented. Some numerical experiments for various projection data were conducted to demonstrate the efficiency of the proposed model and algorithm.

}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/411.html} }
TY - JOUR T1 - Second-Order Total Variation and Primal-Dual Algorithm for CT Image Reconstruction AU - S.-S. Luo, Q. Lv, H.-S. Chen & J.-P. Song JO - International Journal of Numerical Analysis and Modeling VL - 1 SP - 76 EP - 87 PY - 2016 DA - 2016/01 SN - 14 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/ijnam/411.html KW - CT image reconstruction, regularization method, second-order total variation, primal-dual algorithm. AB -

In this paper, we proposed a regularization model based on second-order total variation for CT image reconstruction, which could eliminate the 'staircase' caused by total variation (TV) minimization. Moreover, some properties of second-order total variation were investigated, and a primal-dual algorithm for the proposed model was presented. Some numerical experiments for various projection data were conducted to demonstrate the efficiency of the proposed model and algorithm.

S.-S. Luo, Q. Lv, H.-S. Chen and J.-P. Song. (2016). Second-Order Total Variation and Primal-Dual Algorithm for CT Image Reconstruction. International Journal of Numerical Analysis and Modeling. 14 (1). 76-87. doi:
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