Hyperspectral Unmixing with a Modified Augmented Linear Mixing Model Addressing Spectral Variability
Author:
Affiliation:
1. Agence Spatiale Algérienne, Centre des Techniques Spatiales,Arzew,Algérie
2. IRAP, Université de Toulouse, UPS, CNRS, OMP, CNES,Toulouse,France
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9839665/9839673/09839710.pdf?arnumber=9839710
Reference9 articles.
1. A Penalization-Based NMF Approach for Hyperspectral Unmixing Addressing Spectral Variability with an Additively-Tuned Mixing Model
2. Inertia-Constrained Pixel-by-Pixel Nonnegative Matrix Factorisation: A Hyperspectral Unmixing Method Dealing with Intra-Class Variability
3. Gradient-Based NMF Methods for Hyperspectral Unmixing Addressing Spectral Variability with a Multiplicative-Tuning Linear Mixing Model
4. Partial Linear NMF-Based Unmixing Methods for Detection and Area Estimation of Photovoltaic Panels in Urban Hyperspectral Remote Sensing Data
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2. An ADMM-Based Approach Associated with a Linear Mixing Model Multiplicatively Tuned to Deal with Spectral Variability in Hyperspectral Unmixing;2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS);2024-04-15
3. Addressing Spectral Variability in Hyperspectral Unmixing with a Novel Linear Adaptive Additive Mixing Model and an Associated ADMM-Based Approach;2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS);2024-04-15
4. An Admm-Based Hyperspectral Unmixing Algorithm For A Modified Almm Addressing Spectral Variability;2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS);2024-04-15
5. A Two-Stream Stacked Autoencoder With Inter-Class Separability for Bilinear Hyperspectral Unmixing;IEEE Transactions on Computational Imaging;2024
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