LEADER 01981nam  2200433z- 450 
001 9910346716803321
005 20210211
010   $a1000081665
035   $a(CKB)4920000000094533
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/49739
035   $a(oapen)doab49739
035   $a(EXLCZ)994920000000094533
100   $a20202102d2018      |y         0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aHyperspectral Image Unmixing Incorporating Adjacency Information
210   $cKIT Scientific Publishing$d2018
215   $a1 online resource (XIII, 203 p. p.)
225 1 $aForschungsberichte aus der Industriellen Informationstechnik / Institut für Industrielle Informationstechnik (IIIT), Karlsruher Institut für Technologie
311 08$a3-7315-0788-9 
330   $aWhile 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.
606   $aTechnology: general issues$2bicssc
610   $ablind source separation
610   $aBlinde Quellentrennung
610   $aHyperspectral image processing
610   $aHyperspektrale Bildverarbeitung
610   $aNichtnegative Matrixzerlegung
610   $anonnegative matrix factorization
610   $aspectral unmixing
610   $aSpektrale Entmischung
615  7$aTechnology: general issues
700   $aBauer$b Sebastian$4auth$01292408
906   $aBOOK
912   $a9910346716803321
996   $aHyperspectral Image Unmixing Incorporating Adjacency Information$93022273
997   $aUNINA