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Joint Sparsity Model for Multilook Hyperspectral Image Unmixing

Bieniarz, Jakub and Aguilera, Esteban and Zhu, Xiao Xiang and Müller, Rupert and Reinartz, Peter (2015) Joint Sparsity Model for Multilook Hyperspectral Image Unmixing. IEEE Geoscience and Remote Sensing Letters, 12 (4), pp. 696-700. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/LGRS.2014.2358623 ISSN 1545-598X

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Abstract

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.

Item URL in elib:https://elib.dlr.de/91624/
Document Type:Article
Title:Joint Sparsity Model for Multilook Hyperspectral Image Unmixing
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Bieniarz, Jakubjakub.bieniarz (at) dlr.deUNSPECIFIED
Aguilera, Estebanesteban.aguilera (at) dlr.deUNSPECIFIED
Zhu, Xiao XiangIMFUNSPECIFIED
Müller, Rupertrupert.mueller (at) dlr.deUNSPECIFIED
Reinartz, Peterpeter.reinartz (at) dlr.deUNSPECIFIED
Date:April 2015
Journal or Publication Title:IEEE Geoscience and Remote Sensing Letters
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:12
DOI :10.1109/LGRS.2014.2358623
Page Range:pp. 696-700
Editors:
EditorsEmail
Frery, Alejandro C.acfrery@gmail.com
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1545-598X
Status:Published
Keywords:Joint sparsity, overcomplete spectral dictionary, spectral unmixing
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Vabene++ (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Remote Sensing Technology Institute > SAR Signal Processing
Microwaves and Radar Institute > SAR Technology
Deposited By:INVALID USER
Deposited On:11 Nov 2014 13:45
Last Modified:31 Jul 2019 19:48

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