Hyperspectral Image Unmixing Incorporating Adjacency Information
Abstract
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.
Keywords
Spektrale Entmischung; spectral unmixing; Blinde Quellentrennung; Hyperspectral image processing; Nichtnegative Matrixzerlegung; nonnegative matrix factorization; blind source separation; Hyperspektrale BildverarbeitungISBN
9783731507888Publisher
KIT Scientific PublishingPublisher website
http://www.ksp.kit.edu/Publication date and place
2018Series
Forschungsberichte aus der Industriellen Informationstechnik / Institut für Industrielle Informationstechnik (IIIT), Karlsruher Institut für Technologie,Classification
Technology: general issues


