Assessment of SAR image filtering using adaptive stack filters

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Stack 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 then...

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Autores principales: Buemi, M.E., Mejail, M., Jacobo, J., Frery, A.C., Ramos, H.S.
Formato: Artículo publishedVersion
Publicado: 2011
Materias:
Non-linear filters
SAR image filtering
speckle noise
stack filters
Classification accuracy
Filtered images
Input image
Noiseless images
Noisy versions
Nonlinear filter
Quality indices
SAR Images
Stack filters
Synthetic aperture radar images
Binary images
Boolean functions
Computer vision
Image quality
Nonlinear filtering
Synthetic aperture radar
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_03029743_v7042LNCS_n_p89_Buemi
http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_03029743_v7042LNCS_n_p89_Buemi_oai
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Repositorio Digital de la Universidad de Buenos Aires (UBA) de Universidad de Buenos Aires
id I28-R145-paper_03029743_v7042LNCS_n_p89_Buemi_oai
record_format dspace
spelling I28-R145-paper_03029743_v7042LNCS_n_p89_Buemi_oai2020-10-19 Buemi, M.E. Mejail, M. Jacobo, J. Frery, A.C. Ramos, H.S. 2011 Stack 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 then filtered by a Boolean function, which characterizes the filter. Adaptive stack filters can be designed to be optimal; they are computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work we study the performance of adaptive stack filters when they are applied to Synthetic Aperture Radar (SAR) images. This is done by evaluating the quality of the filtered images through the use of suitable image quality indexes and by measuring the classification accuracy of the resulting images. © 2011 Springer-Verlag. 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_v7042LNCS_n_p89_Buemi info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar Lect. Notes Comput. Sci. 2011;7042 LNCS:89-96 Non-linear filters SAR image filtering speckle noise stack filters Classification accuracy Filtered images Input image Noiseless images Noisy versions Nonlinear filter Quality indices SAR Images speckle noise Stack filters Synthetic aperture radar images Binary images Boolean functions Computer vision Image quality Nonlinear filtering Synthetic aperture radar Assessment of SAR image filtering using adaptive stack filters 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_v7042LNCS_n_p89_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 Non-linear filters
SAR image filtering
speckle noise
stack filters
Classification accuracy
Filtered images
Input image
Noiseless images
Noisy versions
Nonlinear filter
Quality indices
SAR Images
speckle noise
Stack filters
Synthetic aperture radar images
Binary images
Boolean functions
Computer vision
Image quality
Nonlinear filtering
Synthetic aperture radar
spellingShingle Non-linear filters
SAR image filtering
speckle noise
stack filters
Classification accuracy
Filtered images
Input image
Noiseless images
Noisy versions
Nonlinear filter
Quality indices
SAR Images
speckle noise
Stack filters
Synthetic aperture radar images
Binary images
Boolean functions
Computer vision
Image quality
Nonlinear filtering
Synthetic aperture radar
Buemi, M.E.
Mejail, M.
Jacobo, J.
Frery, A.C.
Ramos, H.S.
Assessment of SAR image filtering using adaptive stack filters
topic_facet Non-linear filters
SAR image filtering
speckle noise
stack filters
Classification accuracy
Filtered images
Input image
Noiseless images
Noisy versions
Nonlinear filter
Quality indices
SAR Images
speckle noise
Stack filters
Synthetic aperture radar images
Binary images
Boolean functions
Computer vision
Image quality
Nonlinear filtering
Synthetic aperture radar
description Stack 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 then filtered by a Boolean function, which characterizes the filter. Adaptive stack filters can be designed to be optimal; they are computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work we study the performance of adaptive stack filters when they are applied to Synthetic Aperture Radar (SAR) images. This is done by evaluating the quality of the filtered images through the use of suitable image quality indexes and by measuring the classification accuracy of the resulting images. © 2011 Springer-Verlag.
format Artículo
Artículo
publishedVersion
author Buemi, M.E.
Mejail, M.
Jacobo, J.
Frery, A.C.
Ramos, H.S.
author_facet Buemi, M.E.
Mejail, M.
Jacobo, J.
Frery, A.C.
Ramos, H.S.
author_sort Buemi, M.E.
title Assessment of SAR image filtering using adaptive stack filters
title_short Assessment of SAR image filtering using adaptive stack filters
title_full Assessment of SAR image filtering using adaptive stack filters
title_fullStr Assessment of SAR image filtering using adaptive stack filters
title_full_unstemmed Assessment of SAR image filtering using adaptive stack filters
title_sort assessment of sar image filtering using adaptive stack filters
publishDate 2011
url http://hdl.handle.net/20.500.12110/paper_03029743_v7042LNCS_n_p89_Buemi
http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_03029743_v7042LNCS_n_p89_Buemi_oai
work_keys_str_mv AT buemime assessmentofsarimagefilteringusingadaptivestackfilters
AT mejailm assessmentofsarimagefilteringusingadaptivestackfilters
AT jacoboj assessmentofsarimagefilteringusingadaptivestackfilters
AT freryac assessmentofsarimagefilteringusingadaptivestackfilters
AT ramoshs assessmentofsarimagefilteringusingadaptivestackfilters
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