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Second-order Total Variation and Primal-dual Algorithm for Ct Image Reconstruction
| Content Provider | Semantic Scholar |
|---|---|
| Author | Luo, Shousheng Chen, Heshan Song, Jinping |
| Copyright Year | 2016 |
| 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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.math.ualberta.ca/ijnam/Volume-14-2017/No-1-17/2017-01-05.pdf |
| Alternate Webpage(s) | http://admin.global-sci.org/uploads/Issue/IJNAM/v14n1/2017-01-05_short.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
