Spatial Low-Rank Tensor Factorization and Unmixing of Hyperspectral Images
This work presents a method for hyperspectral image unmixing based on non-negative tensor factorization. While traditional approaches may process spectral information without regard for spatial structures in the dataset, tensor factorization preserves the spectral-spatial relationship which we inten...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2021-06-01
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| Serie: | Computers |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2073-431X/10/6/78 |
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