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An AdaBoost Ensemble Classifier System for Classifying Hyperspectral Data

Ramzi, Pouria and Samadzadegan, Farhad and Reinartz, Peter (2014) An AdaBoost Ensemble Classifier System for Classifying Hyperspectral Data. Photogrammetrie Fernerkundung Geoinformation, 2014 (1), pp. 27-39. E. Schweizerbartsche Verlagsbuchhandlung. DOI: 10.1127/1432-8364/2014/0205 ISSN 1432-8364

Full text not available from this repository.

Official URL: http://www.schweizerbart.de/journals/pfg

Abstract

This paper presents a new multiple classifier system based on AdaBoost to overcome the high dimensionality problem of hyperspectral data. The hyperspectral data are )rst split into a number of band clusters based on the similarities between the contiguous bands, and each band group is considered as an independent data source. The redundant bands in each cluster are then removed using branch and bound technique. Next, a support vector machine (SVM) is applied to each cluster and the outputs are combined using the weights calculated in AdaBoost iterations. Experimental results with AVIRIS and ROSIS datasets clearly demonstrate the superiority of the proposed algorithm in both overall and single class accuracies when compared to other multiple classi)er systems. For AVIRIS data, which contains classes with greater complexity and fewer available training samples, the differences between the overall accuracies of the AdaBoost results are signi)cantly higher compared to those of the other methods, and more pronounced than for the other dataset. In terms of class accuracies, the proposed AdaBoost approach also outperforms other methods in most of the classes.

Item URL in elib:https://elib.dlr.de/88354/
Document Type:Article
Title:An AdaBoost Ensemble Classifier System for Classifying Hyperspectral Data
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Ramzi, PouriaUniversität TeheranUNSPECIFIED
Samadzadegan, Farhadfarhad.samadzadegan (at) dlr.deUNSPECIFIED
Reinartz, PeterPeter.Reinartz (at) dlr.deUNSPECIFIED
Date:February 2014
Journal or Publication Title:Photogrammetrie Fernerkundung Geoinformation
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Volume:2014
DOI :10.1127/1432-8364/2014/0205
Page Range:pp. 27-39
Editors:
EditorsEmail
Kresse, WolfgangHochschule Neubrandenburg
Publisher:E. Schweizerbartsche Verlagsbuchhandlung
ISSN:1432-8364
Status:Published
Keywords:AdaBoost, Band Clustering, Hyperspectral Data, Multiple Classifier Systems, Support Vector Machines
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
Deposited By: Reinartz, Prof. Dr.. Peter
Deposited On:25 Feb 2014 16:17
Last Modified:08 Mar 2018 18:48

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