Hyperspectral Remote Sensing Inversion of Mineral Abundance Based on Sparse Unmixing Method
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8997-3_10
Reference7 articles.
1. Bioucas-Dias, J. M., Plaza, A., Dobigeon, N., Parente, M., Du, Q., Gader, P., & Chanussot, J. (2012). Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(2), 354–379.
2. Borsoi, R. A., Imbiriba, T., Bermudez, J. C. M., & Richard, C. (2018). A fast multiscale spatial regularization for sparse hyperspectral unmixing. IEEE Geoscience and Remote Sensing Letters, 16(4), 598–602.
3. Iordache, M. D., Bioucas-Dias, J. M., & Plaza, A. (2011). Sparse unmixing of hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing, 49(6), 2014–2039.
4. Iordache, M. D., Bioucas-Dias, J. M., & Plaza, A. (2012). Total variation spatial regularization for sparse hyperspectral unmixing. IEEE Transactions on Geoscience and Remote Sensing, 50(11), 4484–4502.
5. Li, H., Feng, R., Wang, L., Zhong, Y., & Zhang, L. (2020). Superpixel-based reweighted low-rank and total variation sparse unmixing for hyperspectral remote sensing imagery. IEEE Transactions on Geoscience and Remote Sensing, 59(1), 629–647.
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