Unsupervised hyperspectral noise estimation and restoration via interband-invariant representation learning
Hyperspectral images (HSIs) acquired from different imaging platforms are inevitably contaminated by multiple types of noise. However, the existing supervised learning based denoising methods often show poor generalizability on data with complex degradation, due to the discrepancy between synthetic...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224006514 |
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