RATIO-BASED SIMILARITY CRITERIA FOR POLARIMETRIC SAR IMAGE

Dealing with multi-look polarimetric synthetic aperture radar (PolSAR) images requires averaging several independent looks to generate a sample covariance matrix of similar target scattering vectors. Along this, estimation of optimal similarity between target scattering vectors is still an open issu...

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Main Authors: H. Aghababaei, G. Ferraioli, V. Pascazio
Format: Article
Language:English
Published: Copernicus Publications 2020-11-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W12-2020/483/2020/isprs-archives-XLII-3-W12-2020-483-2020.pdf
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spelling doaj-625191caba7b43a7b3d9239a44ed37e82020-11-25T04:09:58ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-11-01XLII-3-W12-202048348610.5194/isprs-archives-XLII-3-W12-2020-483-2020RATIO-BASED SIMILARITY CRITERIA FOR POLARIMETRIC SAR IMAGEH. Aghababaei0G. Ferraioli1V. Pascazio2Department of Earth Observation Science, University of Twente, Faculty of Geo-Information Science and Earth Observation, Twente, The NetherlandsDipartimento di Scienze e Tecnologie, Università degli Studi di Napoli “Parthenope”, Napoli, ItalyDipartimento di Ingegneria, Università degli Studi di Napoli “Parthenope,” Napoli, ItalyDealing with multi-look polarimetric synthetic aperture radar (PolSAR) images requires averaging several independent looks to generate a sample covariance matrix of similar target scattering vectors. Along this, estimation of optimal similarity between target scattering vectors is still an open issue. In the literature, this intrinsic task has been mainly addressed in the information-based, geometric-based and detection-based frameworks. However, the derived measures mainly rely on the model assumption such as fully developed speckle and circular complex Gaussian distribution of the scattering vectors, which may not be held in high-resolution images of urban environments. To cope with this possible issue a discriminative model-free measure is proposed, where the similarity of target scattering is computed in the framework of non-local or patch based algorithm. In particular, the discriminative measure is constructed using the ratio between two pre-estimated covariance matrices of the scattering vectors. Experimental validation of the proposed measure is provided using ALOS-PALSAR image and compared with existing criterions in the literature.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W12-2020/483/2020/isprs-archives-XLII-3-W12-2020-483-2020.pdf
collection DOAJ
language English
format Article
sources DOAJ
author H. Aghababaei
G. Ferraioli
V. Pascazio
spellingShingle H. Aghababaei
G. Ferraioli
V. Pascazio
RATIO-BASED SIMILARITY CRITERIA FOR POLARIMETRIC SAR IMAGE
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet H. Aghababaei
G. Ferraioli
V. Pascazio
author_sort H. Aghababaei
title RATIO-BASED SIMILARITY CRITERIA FOR POLARIMETRIC SAR IMAGE
title_short RATIO-BASED SIMILARITY CRITERIA FOR POLARIMETRIC SAR IMAGE
title_full RATIO-BASED SIMILARITY CRITERIA FOR POLARIMETRIC SAR IMAGE
title_fullStr RATIO-BASED SIMILARITY CRITERIA FOR POLARIMETRIC SAR IMAGE
title_full_unstemmed RATIO-BASED SIMILARITY CRITERIA FOR POLARIMETRIC SAR IMAGE
title_sort ratio-based similarity criteria for polarimetric sar image
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2020-11-01
description Dealing with multi-look polarimetric synthetic aperture radar (PolSAR) images requires averaging several independent looks to generate a sample covariance matrix of similar target scattering vectors. Along this, estimation of optimal similarity between target scattering vectors is still an open issue. In the literature, this intrinsic task has been mainly addressed in the information-based, geometric-based and detection-based frameworks. However, the derived measures mainly rely on the model assumption such as fully developed speckle and circular complex Gaussian distribution of the scattering vectors, which may not be held in high-resolution images of urban environments. To cope with this possible issue a discriminative model-free measure is proposed, where the similarity of target scattering is computed in the framework of non-local or patch based algorithm. In particular, the discriminative measure is constructed using the ratio between two pre-estimated covariance matrices of the scattering vectors. Experimental validation of the proposed measure is provided using ALOS-PALSAR image and compared with existing criterions in the literature.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W12-2020/483/2020/isprs-archives-XLII-3-W12-2020-483-2020.pdf
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