@book{Bauer2018, 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.Umfang: XIII, 203 S.Preis: €46.00 | £42.00 | $81.00}, address = {Karlsruhe}, author = {Bauer, Sebastian}, doi = {10.5445/KSP/1000081665}, isbn = {978-3-7315-0788-8}, keyword = {Hyperspektrale Bildverarbeitung, Spektrale Entmischung, Nichtnegative Matrixzerlegung, Blinde Quellentrennung, Hyperspectral image processing, spectral unmixing, nonnegative matrix factorization, blind source separation}, month = {Jul}, pages = {238}, publisher = {KIT Scientific Publishing}, title = {Hyperspectral Image Unmixing Incorporating Adjacency Information}, year = {2018} }