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Image reconstruction algorithm based on variable atomic number matching pursuit
| Content Provider | SAGE Publishing |
|---|---|
| Author | Zhao, Hongtu Chen, Chong Shi, Chenxu |
| Copyright Year | 2016 |
| Abstract | As the most critical part of compressive sensing theory, reconstruction algorithm has an impact on the quality and speed of image reconstruction. After studying some existing convex optimization algorithms and greedy algorithms, we find that convex optimization algorithms should possess higher complexity to achieve higher reconstruction quality. Also, fixed atomic numbers used in most greedy algorithms increase the complexity of reconstruction. In this context, we propose a novel algorithm, called variable atomic number matching pursuit, which can improve the accuracy and speed of reconstruction. Simulation results show that variable atomic number matching pursuit is a fast and stable reconstruction algorithm and better than the other reconstruction algorithms under the same conditions. |
| Related Links | https://journals.sagepub.com/doi/pdf/10.1177/1748301816673074?download=true |
| Starting Page | 103 |
| Ending Page | 109 |
| Page Count | 7 |
| ISSN | 17483018 |
| Issue Number | 2 |
| Volume Number | 11 |
| Journal | Journal of Algorithms & Computational Technology (ACT) |
| e-ISSN | 17483026 |
| DOI | 10.1177/1748301816673074 |
| Language | English |
| Publisher | Sage Publications UK |
| Publisher Date | 2016-10-12 |
| Publisher Place | London |
| Access Restriction | Open |
| Rights Holder | © The Author(s) 2016 |
| Subject Keyword | greedy algorithm compressive sensing convex optimization algorithm Image reconstruction variable atomic number matching pursuit |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Computational Mathematics Numerical Analysis |
