Assessment of SAR image filtering using adaptive stack filters
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...
Autores principales: | , , , , |
---|---|
Formato: | Artículo publishedVersion |
Lenguaje: | Inglés |
Publicado: |
2011
|
Materias: | |
Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_03029743_v7042LNCS_n_p89_Buemi |
Aporte de: |
id |
paperaa:paper_03029743_v7042LNCS_n_p89_Buemi |
---|---|
record_format |
dspace |
spelling |
paperaa:paper_03029743_v7042LNCS_n_p89_Buemi2023-02-10T13:34:28Z Assessment of SAR image filtering using adaptive stack filters Lect. Notes Comput. Sci. 2011;7042 LNCS:89-96 Buemi, M.E. Mejail, M. Jacobo, J. Frery, A.C. Ramos, H.S. 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 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. 2011 info:eu-repo/semantics/article info:ar-repo/semantics/artículo info:eu-repo/semantics/publishedVersion application/pdf eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03029743_v7042LNCS_n_p89_Buemi |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-134 |
collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
language |
Inglés |
orig_language_str_mv |
eng |
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 |
work_keys_str_mv |
AT buemime assessmentofsarimagefilteringusingadaptivestackfilters AT mejailm assessmentofsarimagefilteringusingadaptivestackfilters AT jacoboj assessmentofsarimagefilteringusingadaptivestackfilters AT freryac assessmentofsarimagefilteringusingadaptivestackfilters AT ramoshs assessmentofsarimagefilteringusingadaptivestackfilters |
_version_ |
1759062888282062848 |