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Hyperspectral image unmixing incorporating adjacency information

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Sebastian Bauer

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While the spectral information contained in hyperspectral images is rich, the spatial resolution of such images is in many cases very low. Many pixel spectra are mixtures of pure materials’ spectra and therefore need to be decomposed into their constituents. This work investigates new decomposition methods taking into account spectral, spatial and global 3D adjacency information. This allows for faster and more accurate decomposition results.

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Hyperspectral image unmixing incorporating adjacency information, Sebastian Bauer

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Année de publication: 2018

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Titre: Hyperspectral image unmixing incorporating adjacency information
Langue: Anglais
Auteurs: Sebastian Bauer
Éditeur: KIT Scientific Publishing
Publié: 2018
ISBN10: 3731507889
ISBN13: 9783731507888
Séries: Forschungsberichte aus der industriellen Informationstechnik
Mots clés: Informatique, programmation
Description: While the spectral information contained in hyperspectral images is rich, the spatial resolution of such images is in many cases very low. Many pixel spectra are mixtures of pure materials’ spectra and therefore need to be decomposed into their constituents. This work investigates new decomposition methods taking into account spectral, spatial and global 3D adjacency information. This allows for faster and more accurate decomposition results.