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Remote sensing image gap filling based on spatial-spectral random forests
Remote sensing images play a significant role in global land cover monitoring. However, due to the influence of cloud contamination, optical remote sensing images inevitably contain a large number of missing data, which severely limits their applicability. Existing cloud removal methods generally us...
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| Autors principals: | , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Elsevier
2022-06-01
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| Col·lecció: | Science of Remote Sensing |
| Matèries: | |
| Accés en línia: | http://www.sciencedirect.com/science/article/pii/S2666017222000104 |
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