Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | |
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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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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1817695667877838848 |