The Influence of Noise Intensity in the Nonlinear Spectral Unmixing of Hyperspectral Data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Instrumentation,Geography, Planning and Development
Link
https://link.springer.com/content/pdf/10.1007/s41064-022-00223-x.pdf
Reference44 articles.
1. Altmann Y, Dobigeon N, Tourneret J-Y (2012a) Nonlinearity detection in hyperspectral images using a polynomial post-nonlinear mixing model. IEEE Trans Image Process 22(4):1267–1276
2. Altmann Y, Halimi A, Dobigeon N, Tourneret J-Y (2012b) Supervised nonlinear spectral unmixing using a postnonlinear mixing model for hyperspectral imagery. IEEE Trans Image Process 21(6):3017–3025
3. Ben-Dor E, Notesco G (2016) A simple indicator for estimating the noise level of a hyperspectral data cube for earth observation missions. Acta Astronaut 128:304–312
4. Bioucas-Dias JM, Nascimento JMP (2008) Hyperspectral subspace identification. IEEE Trans Geosci Remote Sens 46(8):2435–2445
5. Bioucas-Dias JM, Plaza A, Dobigeon N, Parente M, Du Q, Gader P, Chanussot J (2012) Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches. IEEE J Sel Top Appl Earth Observ Remote Sens 5(2):354–379. https://doi.org/10.1109/JSTARS.2012.2194696
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