Fisher Vectors for PolSAR Image Classification

Autores
Redolfi, Javier Andrés; Sanchez, Jorge Adrian; Flesia, Ana Georgina
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this letter, we study the application of the Fisher vector (FV) to the problem of pixelwise supervised classification of polarimetric synthetic aperture radar images. This is a challenging problem since information in those images is encoded as complex-valued covariance matrices. We observe that the real parts of these matrices preserve the positive semidefiniteness property of their complex counterpart. Based on this observation, we derive an FV from a mixture of real Wishart densities and integrate it with a Potts-like energy model in order to capture spatial dependencies between neighboring regions. Experimental results on two challenging data sets show the effectiveness of the approach.
Fil: Redolfi, Javier Andrés. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Sanchez, Jorge Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina
Fil: Flesia, Ana Georgina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina
Materia
FISHER VECTORS (FVS)
IMAGE CLASSIFICATION
POLARIMETRIC SYNTHETIC APERTURE RADAR (POLSAR)
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/59999
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Fisher Vectors for PolSAR Image ClassificationRedolfi, Javier AndrésSanchez, Jorge AdrianFlesia, Ana GeorginaFISHER VECTORS (FVS)IMAGE CLASSIFICATIONPOLARIMETRIC SYNTHETIC APERTURE RADAR (POLSAR)https://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1In this letter, we study the application of the Fisher vector (FV) to the problem of pixelwise supervised classification of polarimetric synthetic aperture radar images. This is a challenging problem since information in those images is encoded as complex-valued covariance matrices. We observe that the real parts of these matrices preserve the positive semidefiniteness property of their complex counterpart. Based on this observation, we derive an FV from a mixture of real Wishart densities and integrate it with a Potts-like energy model in order to capture spatial dependencies between neighboring regions. Experimental results on two challenging data sets show the effectiveness of the approach.Fil: Redolfi, Javier Andrés. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sanchez, Jorge Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; ArgentinaFil: Flesia, Ana Georgina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; ArgentinaInstitute of Electrical and Electronics Engineers2017-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/59999Redolfi, Javier Andrés; Sanchez, Jorge Adrian; Flesia, Ana Georgina; Fisher Vectors for PolSAR Image Classification; Institute of Electrical and Electronics Engineers; Ieee Geoscience and Remote Sensing Letters; 14; 11; 11-2017; 2057-20611545-598XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/document/8052593/info:eu-repo/semantics/altIdentifier/doi/10.1109/LGRS.2017.2750800info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:48:11Zoai:ri.conicet.gov.ar:11336/59999instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:48:11.923CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Fisher Vectors for PolSAR Image Classification
title Fisher Vectors for PolSAR Image Classification
spellingShingle Fisher Vectors for PolSAR Image Classification
Redolfi, Javier Andrés
FISHER VECTORS (FVS)
IMAGE CLASSIFICATION
POLARIMETRIC SYNTHETIC APERTURE RADAR (POLSAR)
title_short Fisher Vectors for PolSAR Image Classification
title_full Fisher Vectors for PolSAR Image Classification
title_fullStr Fisher Vectors for PolSAR Image Classification
title_full_unstemmed Fisher Vectors for PolSAR Image Classification
title_sort Fisher Vectors for PolSAR Image Classification
dc.creator.none.fl_str_mv Redolfi, Javier Andrés
Sanchez, Jorge Adrian
Flesia, Ana Georgina
author Redolfi, Javier Andrés
author_facet Redolfi, Javier Andrés
Sanchez, Jorge Adrian
Flesia, Ana Georgina
author_role author
author2 Sanchez, Jorge Adrian
Flesia, Ana Georgina
author2_role author
author
dc.subject.none.fl_str_mv FISHER VECTORS (FVS)
IMAGE CLASSIFICATION
POLARIMETRIC SYNTHETIC APERTURE RADAR (POLSAR)
topic FISHER VECTORS (FVS)
IMAGE CLASSIFICATION
POLARIMETRIC SYNTHETIC APERTURE RADAR (POLSAR)
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this letter, we study the application of the Fisher vector (FV) to the problem of pixelwise supervised classification of polarimetric synthetic aperture radar images. This is a challenging problem since information in those images is encoded as complex-valued covariance matrices. We observe that the real parts of these matrices preserve the positive semidefiniteness property of their complex counterpart. Based on this observation, we derive an FV from a mixture of real Wishart densities and integrate it with a Potts-like energy model in order to capture spatial dependencies between neighboring regions. Experimental results on two challenging data sets show the effectiveness of the approach.
Fil: Redolfi, Javier Andrés. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Sanchez, Jorge Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina
Fil: Flesia, Ana Georgina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina
description In this letter, we study the application of the Fisher vector (FV) to the problem of pixelwise supervised classification of polarimetric synthetic aperture radar images. This is a challenging problem since information in those images is encoded as complex-valued covariance matrices. We observe that the real parts of these matrices preserve the positive semidefiniteness property of their complex counterpart. Based on this observation, we derive an FV from a mixture of real Wishart densities and integrate it with a Potts-like energy model in order to capture spatial dependencies between neighboring regions. Experimental results on two challenging data sets show the effectiveness of the approach.
publishDate 2017
dc.date.none.fl_str_mv 2017-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/59999
Redolfi, Javier Andrés; Sanchez, Jorge Adrian; Flesia, Ana Georgina; Fisher Vectors for PolSAR Image Classification; Institute of Electrical and Electronics Engineers; Ieee Geoscience and Remote Sensing Letters; 14; 11; 11-2017; 2057-2061
1545-598X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/59999
identifier_str_mv Redolfi, Javier Andrés; Sanchez, Jorge Adrian; Flesia, Ana Georgina; Fisher Vectors for PolSAR Image Classification; Institute of Electrical and Electronics Engineers; Ieee Geoscience and Remote Sensing Letters; 14; 11; 11-2017; 2057-2061
1545-598X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/document/8052593/
info:eu-repo/semantics/altIdentifier/doi/10.1109/LGRS.2017.2750800
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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