Speckle reduction with 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 stacks of binary images according to a set of thresholds. Each binary image is the...
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todo:paper_01678655_v36_n1_p281_Buemi2023-10-03T15:05:27Z 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 Bandpass filters Binary images Bins Boolean functions Nonlinear filtering Radar imaging Speckle Synthetic aperture radar Classification accuracy Non linear Optimized filters SAR Images Speckle noise Speckle reduction Stack filters Synthetic aperture radar (SAR) images Adaptive 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 Elsevier B.V. All rights reserved. Fil:Buemi, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_01678655_v36_n1_p281_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 |
Non-linear filters SAR image filtering Speckle noise Stack filters Bandpass filters Binary images Bins Boolean functions Nonlinear filtering Radar imaging Speckle Synthetic aperture radar Classification accuracy Non linear Optimized filters SAR Images Speckle noise Speckle reduction Stack filters Synthetic aperture radar (SAR) images Adaptive filters |
spellingShingle |
Non-linear filters SAR image filtering Speckle noise Stack filters Bandpass filters Binary images Bins Boolean functions Nonlinear filtering Radar imaging Speckle Synthetic aperture radar Classification accuracy Non linear Optimized filters SAR Images Speckle noise Speckle reduction Stack filters Synthetic aperture radar (SAR) images Adaptive 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 Bandpass filters Binary images Bins Boolean functions Nonlinear filtering Radar imaging Speckle Synthetic aperture radar Classification accuracy Non linear Optimized filters SAR Images Speckle noise Speckle reduction Stack filters Synthetic aperture radar (SAR) images Adaptive 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 Elsevier B.V. All rights reserved. |
format |
JOUR |
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_v36_n1_p281_Buemi |
work_keys_str_mv |
AT buemime specklereductionwithadaptivestackfilters AT freryac specklereductionwithadaptivestackfilters AT ramoshs specklereductionwithadaptivestackfilters |
_version_ |
1782030134633562112 |