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Parametric and Nonparametric Methods for SAR Patch Scene Categorization

Gleich, Dusan and Singh, Jagmal and Planinsic, Peter (2015) Parametric and Nonparametric Methods for SAR Patch Scene Categorization. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8 (4), pp. 1623-1634. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/JSTARS.2014.2352337 ISSN 1939-1404

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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6924707


This paper presents synthetic aperture radar (SAR) image categorization based on feature descriptors within the discrete wavelet transform (DWT) domain using nonparametric and parametric features. The first and second moments, Kolmogorov Sinai entropy and coding gain, are used for the nonparametric features within an oriented dual tree complex wavelet transform (2D ODTCWT). A Gauss–Markov random field (GMRF), triplet Markov random field (TMRF), and autobinomial model (ABM) are used for feature extraction using a parametric approach within an image domain. A single parameter of GMRF, TMRF, or ABM is used for characterizing an entire patch; therefore, higher model orders (MOs) are used. A database with 2000 images representing 20 different classes with 100 images per class is used for estimating classification efficiency. A supervised learning stage is implemented within a support vector machine (SVM) using 10% and 20% of the test images per class. The experimental results showed that the nonparametric features achieved better results when compared to the parametric features.

Item URL in elib:https://elib.dlr.de/92780/
Document Type:Article
Additional Information:Article#: 2352337
Title:Parametric and Nonparametric Methods for SAR Patch Scene Categorization
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Gleich, DusanUniversity of Maribor, SloveniaUNSPECIFIED
Singh, Jagmaljagmal.singh (at) dlr.deUNSPECIFIED
Planinsic, PeterUniversity of Maribor, SloveniaUNSPECIFIED
Date:22 May 2015
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1109/JSTARS.2014.2352337
Page Range:pp. 1623-1634
Chanussot, Jocelynjocelyn.chanussot@gipsa-lab.grenoble-inp.fr
Publisher:IEEE - Institute of Electrical and Electronics Engineers
Keywords:Computational modeling Discrete wavelet transforms Entropy Feature extraction Synthetic aperture radar, Discrete wavelet transforms, Entropy, Feature extraction, Synthetic aperture radar
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
Deposited On:01 Dec 2014 18:13
Last Modified:31 Jul 2019 19:49

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