SAR image processing using adaptive stack filter

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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Autores principales: Buemi, María Elena, Mejail, Marta Estela
Publicado: 2010
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Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01678655_v31_n4_p307_Buemi
http://hdl.handle.net/20.500.12110/paper_01678655_v31_n4_p307_Buemi
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spelling paper:paper_01678655_v31_n4_p307_Buemi2023-06-08T15:16:59Z SAR image processing using adaptive stack filter Buemi, María Elena Mejail, Marta Estela Classification Speckle Stack filters Synthetic aperture radar Equivalent number of looks Input image Maximum likelihood classifications Noiseless images Noisy versions Nonlinear filter SAR image processing SAR Images Speckle noise reduction Stack filters Binary images Boolean functions Image classification Imaging systems Maximum likelihood Radar Speckle Synthetic apertures 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 a Boolean function. The Boolean function that characterizes an adaptive stack filter is optimal and is computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work the behavior of adaptive stack filters on synthetic aperture radar (SAR) data is evaluated. With this aim, the equivalent number of looks for stack filtered data are calculated to assess the speckle noise reduction capability of this filter. Then a classification of simulated and real SAR images is carried out on data filtered with a stack filter trained with selected samples. The results of a maximum likelihood classification of these data are evaluated and compared with the results of classifying images previously filtered using the Lee and the Frost filters. © 2009 Elsevier B.V. All rights reserved. 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. 2010 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01678655_v31_n4_p307_Buemi http://hdl.handle.net/20.500.12110/paper_01678655_v31_n4_p307_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
Speckle
Stack filters
Synthetic aperture radar
Equivalent number of looks
Input image
Maximum likelihood classifications
Noiseless images
Noisy versions
Nonlinear filter
SAR image processing
SAR Images
Speckle noise reduction
Stack filters
Binary images
Boolean functions
Image classification
Imaging systems
Maximum likelihood
Radar
Speckle
Synthetic apertures
Synthetic aperture radar
spellingShingle Classification
Speckle
Stack filters
Synthetic aperture radar
Equivalent number of looks
Input image
Maximum likelihood classifications
Noiseless images
Noisy versions
Nonlinear filter
SAR image processing
SAR Images
Speckle noise reduction
Stack filters
Binary images
Boolean functions
Image classification
Imaging systems
Maximum likelihood
Radar
Speckle
Synthetic apertures
Synthetic aperture radar
Buemi, María Elena
Mejail, Marta Estela
SAR image processing using adaptive stack filter
topic_facet Classification
Speckle
Stack filters
Synthetic aperture radar
Equivalent number of looks
Input image
Maximum likelihood classifications
Noiseless images
Noisy versions
Nonlinear filter
SAR image processing
SAR Images
Speckle noise reduction
Stack filters
Binary images
Boolean functions
Image classification
Imaging systems
Maximum likelihood
Radar
Speckle
Synthetic apertures
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 a Boolean function. The Boolean function that characterizes an adaptive stack filter is optimal and is computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work the behavior of adaptive stack filters on synthetic aperture radar (SAR) data is evaluated. With this aim, the equivalent number of looks for stack filtered data are calculated to assess the speckle noise reduction capability of this filter. Then a classification of simulated and real SAR images is carried out on data filtered with a stack filter trained with selected samples. The results of a maximum likelihood classification of these data are evaluated and compared with the results of classifying images previously filtered using the Lee and the Frost filters. © 2009 Elsevier B.V. All rights reserved.
author Buemi, María Elena
Mejail, Marta Estela
author_facet Buemi, María Elena
Mejail, Marta Estela
author_sort Buemi, María Elena
title SAR image processing using adaptive stack filter
title_short SAR image processing using adaptive stack filter
title_full SAR image processing using adaptive stack filter
title_fullStr SAR image processing using adaptive stack filter
title_full_unstemmed SAR image processing using adaptive stack filter
title_sort sar image processing using adaptive stack filter
publishDate 2010
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01678655_v31_n4_p307_Buemi
http://hdl.handle.net/20.500.12110/paper_01678655_v31_n4_p307_Buemi
work_keys_str_mv AT buemimariaelena sarimageprocessingusingadaptivestackfilter
AT mejailmartaestela sarimageprocessingusingadaptivestackfilter
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