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A new approach for endmember extraction and clustering addressing inter- and intra-class variability via multi-scaled-band partitioning

Andreou, Charoula and Rogge, Derek and Müller, Rupert (2016) A new approach for endmember extraction and clustering addressing inter- and intra-class variability via multi-scaled-band partitioning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9 (9), pp. 4215-4231. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/JSTARS.2016.2519610 ISSN 1939-1404

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Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7414396

Abstract

In this paper a new method is introduced for detecting and clustering spectrally similar but physically distinct materials. The method exploits the spectral information by dividing the spectral domain into band subsets whose width vary from broad to narrower wavelength ranges. Multiple candidate endmembers containing intra-class spectral variability are extracted using a maximum volume-based endmember extraction method at each band subset. Spectral clustering of the extracted spectra is also accomplished by using a multi-scaled-band partitioning approach. This allows for the generation of multi-scaled clustering identification vectors that can be used to remove partial mixtures and also be used to derive the final set of endmember bundles which retain inter-class endmember variability. The proposed method was evaluated using simulated and real hyperspectral data and in comparison with well-known methods for extracting a fixed set or multiple sets of endmembers. Results revealed the advantages of the multi-scaled-band partitioning on both multiple endmember extraction and clustering with the latter being an independent module that can be applicable to endmember candidate libraries derived from other methods.

Item URL in elib:https://elib.dlr.de/102306/
Document Type:Article
Title:A new approach for endmember extraction and clustering addressing inter- and intra-class variability via multi-scaled-band partitioning
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Andreou, Charoulacharoula.andreou (at) dlr.deUNSPECIFIED
Rogge, Derekderek.rogge (at) dlr.deUNSPECIFIED
Müller, Rupertrupert.mueller (at) dlr.deUNSPECIFIED
Date:2016
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:9
DOI :10.1109/JSTARS.2016.2519610
Page Range:pp. 4215-4231
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Status:Published
Keywords:endmember extraction, intra-class variability, multi-scaled-band partitioning, spectral clustering, hyperspectral
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
German Remote Sensing Data Center > Land Surface
Deposited By: Andreou, Charoula
Deposited On:22 Jan 2016 14:37
Last Modified:08 Mar 2018 18:32

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