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FrFT-Based Scene Classification of Phase-Gradient InSAR Images and Effective Baseline Dependence

Cagatay, Nazli Deniz and Datcu, Mihai (2015) FrFT-Based Scene Classification of Phase-Gradient InSAR Images and Effective Baseline Dependence. IEEE Geoscience and Remote Sensing Letters, 12 (5), pp. 1131-1135. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/LGRS.2014.2385771 ISSN 1545-598X

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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7024118


In the literature, scene recognition from interferometric synthetic aperture radar (InSAR) images has been mainly focused on the joint use of the backscatter intensity and the coherence between interferometric image pairs. However, the terrain height information residing in the interferometric phase requires further exploration for classification purposes. In this letter, taking the interferometric phase information into account together with the backscatter intensity, the whole complex- valued InSAR image is exploited for feature extraction. In addition, a new complex-valued phase-gradient InSAR (PGInSAR) image is defined. A fractional-Fourier-transform-based feature ex traction, which was proposed for the classification of single-look complex (SLC) SAR images, is adopted for InSAR and PGInSAR images. For patch-based classification, an image database is generated from bistatic pairs acquired from the same terrain with three different effective baselines. The supervised κ-nearest neighbor classification results show that InSAR outperforms SLC by 15%, whereas PGInSAR introduces further 10% improvement over InSAR or a total improvement of 27% over SLC. Moreover, PGInSAR is found to be more robust to effective baseline changes than InSAR, which makes PGInSAR a better candidate for feature extraction.

Item URL in elib:https://elib.dlr.de/96453/
Document Type:Article
Title:FrFT-Based Scene Classification of Phase-Gradient InSAR Images and Effective Baseline Dependence
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Cagatay, Nazli DenizCagatay, Nazli DenizUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Date:May 2015
Journal or Publication Title:IEEE Geoscience and Remote Sensing Letters
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1109/LGRS.2014.2385771
Page Range:pp. 1131-1135
Frery, Alejandro C.Ufal - Universidade Federal de Alagoas, Maceió, AL - Brazil
Publisher:IEEE - Institute of Electrical and Electronics Engineers
Keywords:Effective baseline, feature extraction, fractional Fourier transform (FrFT), interferometric synthetic aperture radar (InSAR), phase gradient
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:16 Jun 2015 10:16
Last Modified:31 Jul 2019 19:53

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