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| Content Provider | Springer Nature Link |
|---|---|
| Author | Li, Yangyang Wei, Ying Wang, Yang Jiao, Licheng |
| Copyright Year | 2013 |
| Abstract | Synthetic aperture radar (SAR) image segmentation is an important problem of the realm of image segmentation. In this study, a novel SAR image segmentation algorithm using a multi-objective evolutionary algorithm based on decomposition with non-local means denoising (MISD) is proposed. The novelty of MISD lies in the following issues: (1) an effective multi-objective method with decomposition to solve SAR image segmentation; (2) in order to denoise the SAR images and retain the details, we employ non-local means to remove the noise. The multi-objective decomposition method makes MISD have lower computational complexity. In order to evaluate the performance of the new method, we compared the results with three other popular segmentation approaches on four simulated and two real SAR images. In our experiments, the new method can always find better results, which means MISD is a promising SAR image segmentation method. |
| Starting Page | 39 |
| Ending Page | 53 |
| Page Count | 15 |
| File Format | |
| ISSN | 15677818 |
| Journal | Natural Computing |
| Volume Number | 13 |
| Issue Number | 1 |
| e-ISSN | 15729796 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2013-10-15 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Multi-objective evolutionary algorithm Clustering SAR image segmentation Non-local means Decomposition approach Theory of Computation Evolutionary Biology Processor Architectures Artificial Intelligence (incl. Robotics) Statistical Physics, Dynamical Systems and Complexity |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science Applications |
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