Bieniarz, Jakub und Aguilera, Esteban und Zhu, Xiao Xiang und Müller, Rupert und Reinartz, Peter (2015) Joint Sparsity Model for Multilook Hyperspectral Image Unmixing. IEEE Geoscience and Remote Sensing Letters, 12 (4), Seiten 696-700. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/LGRS.2014.2358623. ISSN 1545-598X.
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Kurzfassung
Recent work on hyperspectral image (HSI) unmixing has addressed the use of overcomplete dictionaries by employing sparse models. In essence, this approach exploits the fact that HSI pixels can be associated with a small number of constituent pure materials. However, unlike traditional least-squares-based methods, sparsity-based techniques do not require a preselection of endmembers and are thus able to simultaneously estimate the underlying active materials along with their respective abundances. In addition, this perspective has been extended so as to exploit the spatial homogeneity of abundance vectors. As a result, these techniques have been reported to provide improved estimation accuracy. In this letter, we present an alternative approach that is able to relax, yet exploit, the assumption of spatial homogeneity by introducing a model that captures both similarities and differences between neighboring abundances. In order to validate this approach, we analyze our model using simulated as well as real hyperspectral data acquired by the HyMap sensor.
elib-URL des Eintrags: | https://elib.dlr.de/91624/ | ||||||||||||||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||||||
Titel: | Joint Sparsity Model for Multilook Hyperspectral Image Unmixing | ||||||||||||||||||||||||
Autoren: |
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Datum: | April 2015 | ||||||||||||||||||||||||
Erschienen in: | IEEE Geoscience and Remote Sensing Letters | ||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||||||
Band: | 12 | ||||||||||||||||||||||||
DOI: | 10.1109/LGRS.2014.2358623 | ||||||||||||||||||||||||
Seitenbereich: | Seiten 696-700 | ||||||||||||||||||||||||
Herausgeber: |
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Verlag: | IEEE - Institute of Electrical and Electronics Engineers | ||||||||||||||||||||||||
ISSN: | 1545-598X | ||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||
Stichwörter: | Joint sparsity, overcomplete spectral dictionary, spectral unmixing | ||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||
HGF - Programm: | Verkehr | ||||||||||||||||||||||||
HGF - Programmthema: | Verkehrsmanagement (alt) | ||||||||||||||||||||||||
DLR - Schwerpunkt: | Verkehr | ||||||||||||||||||||||||
DLR - Forschungsgebiet: | V VM - Verkehrsmanagement | ||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | V - Vabene++ (alt) | ||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > Photogrammetrie und Bildanalyse Institut für Methodik der Fernerkundung > SAR-Signalverarbeitung Institut für Hochfrequenztechnik und Radarsysteme > SAR-Technologie | ||||||||||||||||||||||||
Hinterlegt von: | UNGÜLTIGER BENUTZER | ||||||||||||||||||||||||
Hinterlegt am: | 11 Nov 2014 13:45 | ||||||||||||||||||||||||
Letzte Änderung: | 27 Nov 2023 12:38 |
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