Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.

Detalhes bibliográficos
Autor(a) principal: GAMBA, S. R. H.
Data de Publicação: 2011
Outros Autores: SANO, E. E.
Idioma: por
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1152498
Resumo: ABSTRACT -This study deals with the identification of vessels in airborne synthetic aperture radar (SAR) images. The objective is to identify the optimal GIS-based integration approaches, image enhancements, morphological filters, classifiers and processors that enable better identification of ships in SAR images from the coastal areas of Brazil. The methodology included the analysis of five digital images from three study areas (Port of Tubarão (Es), Port of Santos (SP), and Snake Island (RS)) were exported to MS Excel? spreadsheet and statistical packages SPSS? and MINITAB? to be analyzed statistically. The images were further processed using ENVI 4.5 on different highlights (2% linear, Gaussian, equalization, square root and contrast from 50 to 200), morphological filters (dilation, erosion, opening and closing), non-supervised classifiers (ISODATA and Kmeans clustering), supervised classifiers (parallelepiped, minimum distance, Mahalanobis distance, maximum likelihood, spectral angle map, divergence of spectral information, binary encoding and support vector machine) and processors (by decorrelation highlight, saturation and synthetic color image). Results of this study showed that the the most appropriate SAR image to identify vessels was the L-band with HH, VV and VH, or HH, VV and HV polarizations, followed by application of contrast enhancement of 50-200, morphological opening filter and classifier support vector machine or synthetic color image processor.
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spelling Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.Porto MarítimoSensoriamento RemotoRadarRemote sensingABSTRACT -This study deals with the identification of vessels in airborne synthetic aperture radar (SAR) images. The objective is to identify the optimal GIS-based integration approaches, image enhancements, morphological filters, classifiers and processors that enable better identification of ships in SAR images from the coastal areas of Brazil. The methodology included the analysis of five digital images from three study areas (Port of Tubarão (Es), Port of Santos (SP), and Snake Island (RS)) were exported to MS Excel? spreadsheet and statistical packages SPSS? and MINITAB? to be analyzed statistically. The images were further processed using ENVI 4.5 on different highlights (2% linear, Gaussian, equalization, square root and contrast from 50 to 200), morphological filters (dilation, erosion, opening and closing), non-supervised classifiers (ISODATA and Kmeans clustering), supervised classifiers (parallelepiped, minimum distance, Mahalanobis distance, maximum likelihood, spectral angle map, divergence of spectral information, binary encoding and support vector machine) and processors (by decorrelation highlight, saturation and synthetic color image). Results of this study showed that the the most appropriate SAR image to identify vessels was the L-band with HH, VV and VH, or HH, VV and HV polarizations, followed by application of contrast enhancement of 50-200, morphological opening filter and classifier support vector machine or synthetic color image processor.SÉRGIO ROBERTO HORST GAMBA, UNIVERSIDADE DE BRASÍLIA; EDSON EYJI SANO, CPAC.GAMBA, S. R. H.SANO, E. E.2023-03-20T12:51:33Z2023-03-20T12:51:33Z2023-03-202011Artigo em anais e proceedingsinfo:eu-repo/semantics/publishedVersionp. 8310-8317In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1152498porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2023-03-20T12:51:33Zoai:www.alice.cnptia.embrapa.br:doc/1152498Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542023-03-20T12:51:33Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
title Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
spellingShingle Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
GAMBA, S. R. H.
Porto Marítimo
Sensoriamento Remoto
Radar
Remote sensing
title_short Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
title_full Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
title_fullStr Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
title_full_unstemmed Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
title_sort Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
author GAMBA, S. R. H.
author_facet GAMBA, S. R. H.
SANO, E. E.
author_role author
author2 SANO, E. E.
author2_role author
dc.contributor.none.fl_str_mv SÉRGIO ROBERTO HORST GAMBA, UNIVERSIDADE DE BRASÍLIA; EDSON EYJI SANO, CPAC.
dc.contributor.author.fl_str_mv GAMBA, S. R. H.
SANO, E. E.
dc.subject.por.fl_str_mv Porto Marítimo
Sensoriamento Remoto
Radar
Remote sensing
topic Porto Marítimo
Sensoriamento Remoto
Radar
Remote sensing
description ABSTRACT -This study deals with the identification of vessels in airborne synthetic aperture radar (SAR) images. The objective is to identify the optimal GIS-based integration approaches, image enhancements, morphological filters, classifiers and processors that enable better identification of ships in SAR images from the coastal areas of Brazil. The methodology included the analysis of five digital images from three study areas (Port of Tubarão (Es), Port of Santos (SP), and Snake Island (RS)) were exported to MS Excel? spreadsheet and statistical packages SPSS? and MINITAB? to be analyzed statistically. The images were further processed using ENVI 4.5 on different highlights (2% linear, Gaussian, equalization, square root and contrast from 50 to 200), morphological filters (dilation, erosion, opening and closing), non-supervised classifiers (ISODATA and Kmeans clustering), supervised classifiers (parallelepiped, minimum distance, Mahalanobis distance, maximum likelihood, spectral angle map, divergence of spectral information, binary encoding and support vector machine) and processors (by decorrelation highlight, saturation and synthetic color image). Results of this study showed that the the most appropriate SAR image to identify vessels was the L-band with HH, VV and VH, or HH, VV and HV polarizations, followed by application of contrast enhancement of 50-200, morphological opening filter and classifier support vector machine or synthetic color image processor.
publishDate 2011
dc.date.none.fl_str_mv 2011
2023-03-20T12:51:33Z
2023-03-20T12:51:33Z
2023-03-20
dc.type.driver.fl_str_mv Artigo em anais e proceedings
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1152498
identifier_str_mv In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1152498
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv p. 8310-8317
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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