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Reference TypeConference Proceedings
Repositorysid.inpe.br/sibgrapi@80/2007/08.03.17.13
Metadatasid.inpe.br/sibgrapi@80/2007/08.03.17.13.13
Sitesibgrapi.sid.inpe.br
Citation KeyBuemiMejaJacoGamb:2007:ImSAIm
Author1 Buemi, María Elena
2 Mejail, Marta
3 Jacobo, Julio
4 Gambini, Juliana
Affiliation1 Universidad de Buenos Aires-Facultad de Ciencias Exactas y Naturales-Departamento de Computacion
2 Universidad de Buenos Aires-Facultad de Ciencias Exactas y Naturales-Departamento de Computacion
3 Universidad de Buenos Aires-Facultad de Ciencias Exactas y Naturales-Departamento de Computacion
4 Universidad de Buenos Aires-Facultad de Ciencias Exactas y Naturales-Departamento de Computacion
TitleImprovement in SAR Image Classification using Adaptive Stack Filters
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)
Year2007
EditorFalcão, Alexandre Xavier
Lopes, Hélio Côrtes Vieira
Book TitleProceedings
DateOct. 7-10, 2007
Publisher CityLos Alamitos
PublisherIEEE Computer Society
Conference LocationBelo Horizonte
KeywordsStack Filter - SAR - Speckle -Classification.
AbstractStack filters are a special case of non-linear filters. They have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into several binary images according to a set of thresholds. Each binary image is filtered by a Boolean function. The Boolean function that characterizes an adaptive stack filter is optimal and is computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work the behavior of adaptive stack filters is evaluated for the classification of Synthetic Aperture Radar (SAR) images, which are affected by speckle noise. With this aim it was carried out experiment in which simulated and real images are generated and then filtered with a stack filter trained with one of them. The results of their Maximum Likelihood classification are evaluated and then are compared with the results of classifying the images without previous filtering.
Languageen
Tertiary TypeFull Paper
FormatPrinted, On-line.
Size501 KiB
Number of Files1
Target Filesib_stack_filter.pdf
Last Update2007:08.03.17.13.11 sid.inpe.br/banon/2001/03.30.15.38 administrator
Metadata Last Update2020:02.19.03.06.19 sid.inpe.br/banon/2001/03.30.15.38 administrator {D 2007}
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History2008-07-17 14:09:43 :: mebuemi@gmail.com -> administrator ::
2009-08-13 20:38:31 :: administrator -> banon ::
2010-08-28 20:02:29 :: banon -> administrator ::
2020-02-19 03:06:19 :: administrator -> :: 2007
Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume
Access Date2020, Oct. 26

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