SSMM: Semi-supervised manifold method with spatial-spectral self-training and regularized metric constraints for hyperspectral image dimensionality reduction
Manifold learning is an important technique for dimensionality reduction in hyperspectral images. It maps data from high dimensions to low dimensions to eliminate redundant information. However, the existing manifold learning methods cannot effectively solve the problem of lacking label information...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225000202 |
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