Por favor, use este identificador para citar o enlazar este ítem: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1152498
Título: Identificação de embarcações em imagens aerotransportadas de radar de abertura sintética na área marítima do Brasil.
Autor: GAMBA, S. R. H.
SANO, E. E.
Afiliación: SÉRGIO ROBERTO HORST GAMBA, UNIVERSIDADE DE BRASÍLIA; EDSON EYJI SANO, CPAC.
Año: 2011
Referencia: In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011.
Páginas: p. 8310-8317
Descripción: 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.
Thesagro: Porto Marítimo
Sensoriamento Remoto
Radar
NAL Thesaurus: Remote sensing
Tipo de Material: Artigo em anais e proceedings
Acceso: openAccess
Aparece en las colecciones:Artigo em anais de congresso (CPAC)

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