Adaptive stack filters in speckled imagery

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 filte...

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Detalles Bibliográficos
Autores principales: Buemi, M.E., Mejail, M.E., Jacobo, J.C., Gambini, M.J.
Formato: CONF
Materias:
Classification
Sinthetic aperture radar
Speckle
Stack filter
Corrupted images
Ideal images
Input image
Maximum likelihood classifications
Monte Carlo experiments
Nonlinear filter
Simulated images
Speckle noise
Stack filters
Binary images
Boolean functions
Computer vision
Maximum likelihood
Radar
Synthetic aperture radar
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_97288654_v1_n_p33_Buemi
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_97288654_v1_n_p33_Buemi
record_format dspace
spelling todo:paper_97288654_v1_n_p33_Buemi2023-10-03T16:42:37Z Adaptive stack filters in speckled imagery Buemi, M.E. Mejail, M.E. Jacobo, J.C. Gambini, M.J. Classification Sinthetic aperture radar Speckle Stack filter Classification Corrupted images Ideal images Input image Maximum likelihood classifications Monte Carlo experiments Nonlinear filter Simulated images Speckle noise Stack filters Binary images Boolean functions Computer vision Maximum likelihood Radar Speckle 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 filtered by using a boolean function. Adaptive stack filters are optimized filters that compute a boolean function by using a corrupted image and ideal image without noise. In this work the behaviour of an adaptive stack filter is evaluated for the classification of synthetic apreture radar (SAR) images, which are affected by speckle noise. With this aim it is carried out a Monte Carlo experiment in which simulated 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. Fil:Buemi, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Mejail, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Gambini, M.J. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_97288654_v1_n_p33_Buemi
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Classification
Sinthetic aperture radar
Speckle
Stack filter
Classification
Corrupted images
Ideal images
Input image
Maximum likelihood classifications
Monte Carlo experiments
Nonlinear filter
Simulated images
Speckle noise
Stack filters
Binary images
Boolean functions
Computer vision
Maximum likelihood
Radar
Speckle
Synthetic aperture radar
spellingShingle Classification
Sinthetic aperture radar
Speckle
Stack filter
Classification
Corrupted images
Ideal images
Input image
Maximum likelihood classifications
Monte Carlo experiments
Nonlinear filter
Simulated images
Speckle noise
Stack filters
Binary images
Boolean functions
Computer vision
Maximum likelihood
Radar
Speckle
Synthetic aperture radar
Buemi, M.E.
Mejail, M.E.
Jacobo, J.C.
Gambini, M.J.
Adaptive stack filters in speckled imagery
topic_facet Classification
Sinthetic aperture radar
Speckle
Stack filter
Classification
Corrupted images
Ideal images
Input image
Maximum likelihood classifications
Monte Carlo experiments
Nonlinear filter
Simulated images
Speckle noise
Stack filters
Binary images
Boolean functions
Computer vision
Maximum likelihood
Radar
Speckle
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 filtered by using a boolean function. Adaptive stack filters are optimized filters that compute a boolean function by using a corrupted image and ideal image without noise. In this work the behaviour of an adaptive stack filter is evaluated for the classification of synthetic apreture radar (SAR) images, which are affected by speckle noise. With this aim it is carried out a Monte Carlo experiment in which simulated 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.
format CONF
author Buemi, M.E.
Mejail, M.E.
Jacobo, J.C.
Gambini, M.J.
author_facet Buemi, M.E.
Mejail, M.E.
Jacobo, J.C.
Gambini, M.J.
author_sort Buemi, M.E.
title Adaptive stack filters in speckled imagery
title_short Adaptive stack filters in speckled imagery
title_full Adaptive stack filters in speckled imagery
title_fullStr Adaptive stack filters in speckled imagery
title_full_unstemmed Adaptive stack filters in speckled imagery
title_sort adaptive stack filters in speckled imagery
url http://hdl.handle.net/20.500.12110/paper_97288654_v1_n_p33_Buemi
work_keys_str_mv AT buemime adaptivestackfiltersinspeckledimagery
AT mejailme adaptivestackfiltersinspeckledimagery
AT jacobojc adaptivestackfiltersinspeckledimagery
AT gambinimj adaptivestackfiltersinspeckledimagery
_version_ 1782026617723289600

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