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		<label>7877</label>
		<citationkey>VieiraYanaFrerSant:1996:SiAnCl</citationkey>
		<title>Um sistema de analise e classificacao estatisticas para imagens SAR</title>
		<year>1996</year>
		<secondarydate>19980131</secondarydate>
		<secondarytype>PRE CI</secondarytype>
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		<size>342 KiB</size>
		<author>Vieira, Pedro Ronalt,</author>
		<author>Yanasse, Corina da Costa Freitas,</author>
		<author>Frery, Alejandro Cesar Orgambide,</author>
		<author>Sant'Anna, Sidnei Joćo Siqueira,</author>
		<group>DSR-INPE-MCT-BR</group>
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		<group>DPI-INPE-MCT-BR</group>
		<conferencename>Latin-American Seminar on Radar Sensing, 1.</conferencename>
		<conferencelocation>Buenos Aires, AR</conferencelocation>
		<date>2-4 dec. 1996</date>
		<volume>ESA SP-407</volume>
		<pages>179-185</pages>
		<organization>CONAE/INPE/ESA/SELPER/CIDA/DI-UFPe</organization>
		<transferableflag>1</transferableflag>
		<contenttype>External Contribution</contenttype>
		<versiontype>publisher</versiontype>
		<keywords>Synthetic Aperture Radar (SAR), classification.</keywords>
		<abstract>The objective of this paper is to present an integrated system for Synthetic Aperture Radar (SAR)data processing, classification and analysis, based on the statistical properties of SAR data. The classification is performed using the Maximum Likelihood (MaxVer)classifier and the Iterated Conditional Modes (ICM)contextual classifier. The system showed to be very efficient for the classification of images from two different sensors. The classification results indicate that a more precise classification is achieved using the distributions which are suitable for SAR data, when compared with classical methods that use Gaussian distributions. It is also shown that the ICM classifications present results that are usually twice higher than those obtained using the MaxVer method.</abstract>
		<area>SRE</area>
		<language>pt</language>
		<targetfile>Comut 018743.pdf</targetfile>
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