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SAR Image Categorization Using Parametric and Nonparametric Approaches Within a Dual Tree CWT

Planinsic, Peter and Singh, Jagmal and Dusan, Gleich (2014) SAR Image Categorization Using Parametric and Nonparametric Approaches Within a Dual Tree CWT. IEEE Geoscience and Remote Sensing Letters, 11 (10), pp. 1757-1761. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/LGRS.2014.2308328 ISBN 1545-598X ISSN 1545-598X

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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6787006

Abstract

This letter presents synthetic aperture radar (SAR) image classification based on feature descriptors within the discrete wavelet transform (DWT) domain using parametric and nonparametric features. The DWT enables an efficient multiresolution description of SAR images due to its geometric and stochastic features. A 2-D DWT, a real 2-D oriented dual tree wavelet transform (2-D RODTWT) and an oriented dual tree complex wavelet transform (2-D ODTCWT) were used for the estimation of subband features. First and second moments, entropy, coding gain, and fractal dimension were used for the nonparametric approach. A parametric approach considers a Gauss Markov Random Field model for feature extraction. A database with 2000 images representing 20 different classes with 100 images per class was used for classification efficiency assessment. Several SAR scenes were divided into small patches with dimension of 200 × 200 pixels. 10% and 20% of the test images per class were used during the learning stage. Supervised learning using a support vector machine was used for all experiments. The experimental results showed that the proposed methods had superior performances compared with (GLCM) and log comulants of Fourier transform. Amongst the proposed methods, the nonparametric features within oriented dual tree complex wavelet transform gave the best results for classes when categorizing SAR images.

Item URL in elib:https://elib.dlr.de/90295/
Document Type:Article
Title:SAR Image Categorization Using Parametric and Nonparametric Approaches Within a Dual Tree CWT
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Planinsic, PeterUniversity of Maribor, SloveniaUNSPECIFIED
Singh, Jagmaljagmal.singh (at) dlr.deUNSPECIFIED
Dusan, Gleichdusan.gleich (at) uni-mb.siUNSPECIFIED
Date:May 2014
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:11
DOI :10.1109/LGRS.2014.2308328
Page Range:pp. 1757-1761
Editors:
EditorsEmail
Frery, Alejandro C.Ufal - Universidade Federal de Alagoas, Brazil
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1545-598X
ISBN:1545-598X
Status:Published
Keywords:Data mining, feature extraction, image texture analysis, support vector machines (SVMs), wavelet transforms
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 By:INVALID USER
Deposited On:26 Sep 2014 17:14
Last Modified:31 Jul 2019 19:47

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