SAR image segmentation using level sets and region competition under the GH model
Synthetic Aperture Radar (SAR) images are dificult to segment due to their characteristic noise, called speckle, which is multiplicative, non-gaussian and has a low signal to noise ratio. In this work we use the GH distribution to model the SAR data from the different regions of the image. We estima...
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Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_03029743_v5856LNCS_n_p153_Buemi http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_03029743_v5856LNCS_n_p153_Buemi_oai |
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I28-R145-paper_03029743_v5856LNCS_n_p153_Buemi_oai2020-10-19 Buemi, M.E. Goussies, N. Jacobo, J. Mejail, M. 2009 Synthetic Aperture Radar (SAR) images are dificult to segment due to their characteristic noise, called speckle, which is multiplicative, non-gaussian and has a low signal to noise ratio. In this work we use the GH distribution to model the SAR data from the different regions of the image. We estimate their statistical parameters and use them in a segmentation algorithm based on multiregion competition. We then apply this algorithm to segment simulated as well as real SAR images and evaluate the accuracy of the segmentation results obtained. © 2009 Springer-Verlag Berlin Heidelberg. Fil:Buemi, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Mejail, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. application/pdf http://hdl.handle.net/20.500.12110/paper_03029743_v5856LNCS_n_p153_Buemi info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar Lect. Notes Comput. Sci. 2009;5856 LNCS:153-160 GHdistribution Level set Multiregion competition SAR images Segmentation GHdistribution Level Set Multiregion competition SAR Images Segmentation Algorithms Competition Computer applications Computer vision Imaging systems Signal to noise ratio Synthetic aperture radar Image segmentation SAR image segmentation using level sets and region competition under the GH model info:eu-repo/semantics/article info:ar-repo/semantics/artículo info:eu-repo/semantics/publishedVersion http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_03029743_v5856LNCS_n_p153_Buemi_oai |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-145 |
collection |
Repositorio Digital de la Universidad de Buenos Aires (UBA) |
topic |
GHdistribution Level set Multiregion competition SAR images Segmentation GHdistribution Level Set Multiregion competition SAR Images Segmentation Algorithms Competition Computer applications Computer vision Imaging systems Signal to noise ratio Synthetic aperture radar Image segmentation |
spellingShingle |
GHdistribution Level set Multiregion competition SAR images Segmentation GHdistribution Level Set Multiregion competition SAR Images Segmentation Algorithms Competition Computer applications Computer vision Imaging systems Signal to noise ratio Synthetic aperture radar Image segmentation Buemi, M.E. Goussies, N. Jacobo, J. Mejail, M. SAR image segmentation using level sets and region competition under the GH model |
topic_facet |
GHdistribution Level set Multiregion competition SAR images Segmentation GHdistribution Level Set Multiregion competition SAR Images Segmentation Algorithms Competition Computer applications Computer vision Imaging systems Signal to noise ratio Synthetic aperture radar Image segmentation |
description |
Synthetic Aperture Radar (SAR) images are dificult to segment due to their characteristic noise, called speckle, which is multiplicative, non-gaussian and has a low signal to noise ratio. In this work we use the GH distribution to model the SAR data from the different regions of the image. We estimate their statistical parameters and use them in a segmentation algorithm based on multiregion competition. We then apply this algorithm to segment simulated as well as real SAR images and evaluate the accuracy of the segmentation results obtained. © 2009 Springer-Verlag Berlin Heidelberg. |
format |
Artículo Artículo publishedVersion |
author |
Buemi, M.E. Goussies, N. Jacobo, J. Mejail, M. |
author_facet |
Buemi, M.E. Goussies, N. Jacobo, J. Mejail, M. |
author_sort |
Buemi, M.E. |
title |
SAR image segmentation using level sets and region competition under the GH model |
title_short |
SAR image segmentation using level sets and region competition under the GH model |
title_full |
SAR image segmentation using level sets and region competition under the GH model |
title_fullStr |
SAR image segmentation using level sets and region competition under the GH model |
title_full_unstemmed |
SAR image segmentation using level sets and region competition under the GH model |
title_sort |
sar image segmentation using level sets and region competition under the gh model |
publishDate |
2009 |
url |
http://hdl.handle.net/20.500.12110/paper_03029743_v5856LNCS_n_p153_Buemi http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_03029743_v5856LNCS_n_p153_Buemi_oai |
work_keys_str_mv |
AT buemime sarimagesegmentationusinglevelsetsandregioncompetitionundertheghmodel AT goussiesn sarimagesegmentationusinglevelsetsandregioncompetitionundertheghmodel AT jacoboj sarimagesegmentationusinglevelsetsandregioncompetitionundertheghmodel AT mejailm sarimagesegmentationusinglevelsetsandregioncompetitionundertheghmodel |
_version_ |
1766026686258741248 |