Abstract
The classification method of SAR image based on support vector machine (SVM) with extracting the gray feature, texture feature (gray co-occurrence matrix) was proposed. Compared the results of different kernel functions with the result of maximum likelihood classifier, this approach was proved to be able to classify those patterns that can't be distinguished exactly by the maximum likelihood classifier. On the other hand, experimental results showed the classification precision of SVM with linear kernel function is higher than that with Gauss kernel function.
| Original language | English |
|---|---|
| Pages (from-to) | 444-449 |
| Number of pages | 6 |
| Journal | Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology |
| Volume | 26 |
| Issue number | SUPPL. |
| State | Published - Sep 2004 |
Keywords
- Classification
- SAR
- Support vector machine
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