Speckle reduction with 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 stacks of binary images according to a set of thresholds. Each binary image is the...

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Detalles Bibliográficos
Autores principales: Buemi, M.E., Frery, A.C., Ramos, H.S.
Formato: INPR
Lenguaje:English
Materias:
Non-linear filters
SAR image filtering
Speckle noise
Stack filters
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_01678655_v_n_p_Buemi
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_01678655_v_n_p_Buemi
record_format dspace
spelling todo:paper_01678655_v_n_p_Buemi2023-10-03T15:05:28Z Speckle reduction with adaptive stack filters Buemi, M.E. Frery, A.C. Ramos, H.S. Non-linear filters SAR image filtering Speckle noise 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 stacks of 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 computed by training using a prototype (ideal) image and its corrupted version, leading to optimized filters with respect to a loss function. In this work we propose the use of training with selected samples for the estimation of the optimal Boolean function. We study the performance of adaptive stack filters when they are applied to speckled imagery, in particular 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. We used SAR images as input, since they are affected by speckle noise that makes classification a difficult task. © 2013. Fil:Buemi, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. INPR English info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_01678655_v_n_p_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 English
orig_language_str_mv English
topic Non-linear filters
SAR image filtering
Speckle noise
Stack filters
spellingShingle Non-linear filters
SAR image filtering
Speckle noise
Stack filters
Buemi, M.E.
Frery, A.C.
Ramos, H.S.
Speckle reduction with adaptive stack filters
topic_facet Non-linear filters
SAR image filtering
Speckle noise
Stack filters
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 stacks of 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 computed by training using a prototype (ideal) image and its corrupted version, leading to optimized filters with respect to a loss function. In this work we propose the use of training with selected samples for the estimation of the optimal Boolean function. We study the performance of adaptive stack filters when they are applied to speckled imagery, in particular 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. We used SAR images as input, since they are affected by speckle noise that makes classification a difficult task. © 2013.
format INPR
author Buemi, M.E.
Frery, A.C.
Ramos, H.S.
author_facet Buemi, M.E.
Frery, A.C.
Ramos, H.S.
author_sort Buemi, M.E.
title Speckle reduction with adaptive stack filters
title_short Speckle reduction with adaptive stack filters
title_full Speckle reduction with adaptive stack filters
title_fullStr Speckle reduction with adaptive stack filters
title_full_unstemmed Speckle reduction with adaptive stack filters
title_sort speckle reduction with adaptive stack filters
url http://hdl.handle.net/20.500.12110/paper_01678655_v_n_p_Buemi
work_keys_str_mv AT buemime specklereductionwithadaptivestackfilters
AT freryac specklereductionwithadaptivestackfilters
AT ramoshs specklereductionwithadaptivestackfilters
_version_ 1807314952098152448

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