Relaxed Collaborative Representation With Low-Rank and Sparse Matrix Decomposition for Hyperspectral Anomaly Detection
Hyperspectral anomaly detection methods based on representation model have drawn more attention due to their simplicity and efficiency. The traditional collaborative representation (CR) model does not consider the differences between features, resulting in insufficient feature utilization. In additi...
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| Asıl Yazarlar: | , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
IEEE
2022-01-01
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| Seri Bilgileri: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Konular: | |
| Online Erişim: | https://ieeexplore.ieee.org/document/9837418/ |
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