Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images

Autores
Nemer, Karim Alejandra; Pucheta, Martín Alejo; Flesia, Ana Georgina
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The automated detection of coasts, riverbanks, and polynyas from synthetic aperture radar images is a difficult image processing task due to speckle noise. In this work we present a novel Fuzzy-Wavelet framework for bordeline region detection in SAR images. Our technique is based on a combination of Wavelet denoising and Fuzzy Logic which boost decision-making on noisy and poorly defined environments. Unlike most recent filtering-detection algorithms, we do not apply hypothesis tests (Wilcoxon-Mann Whitney-G0) to label the edge point candidates one by one, instead we construct a fuzzy map from wavelet denoised image and extract their borderline. We compare our algorithm performance with the popular Frost-Sobel approach and a version of Canny’s algorithm with data-dependent parameters, over a database of real polynyas and coastline simulated images under the multiplicative model. The experimental results are evaluated by comparing Pratt’s Figure of Merit index of edge map quality. In almost all test images our algorithm outperforms the standard algorithms in quality and speed.
Fil: Nemer, Karim Alejandra. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina
Fil: Pucheta, Martín Alejo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina
Fil: Flesia, Ana Georgina. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina
Materia
EDGE DETECTION
ENVIRONMENTAL SUSTAINABILITY ENGINEERING
FUZZY LOGIC
SAR IMAGES
WAVELETS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/58453
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/58453
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar imagesNemer, Karim AlejandraPucheta, Martín AlejoFlesia, Ana GeorginaEDGE DETECTIONENVIRONMENTAL SUSTAINABILITY ENGINEERINGFUZZY LOGICSAR IMAGESWAVELETShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The automated detection of coasts, riverbanks, and polynyas from synthetic aperture radar images is a difficult image processing task due to speckle noise. In this work we present a novel Fuzzy-Wavelet framework for bordeline region detection in SAR images. Our technique is based on a combination of Wavelet denoising and Fuzzy Logic which boost decision-making on noisy and poorly defined environments. Unlike most recent filtering-detection algorithms, we do not apply hypothesis tests (Wilcoxon-Mann Whitney-G0) to label the edge point candidates one by one, instead we construct a fuzzy map from wavelet denoised image and extract their borderline. We compare our algorithm performance with the popular Frost-Sobel approach and a version of Canny’s algorithm with data-dependent parameters, over a database of real polynyas and coastline simulated images under the multiplicative model. The experimental results are evaluated by comparing Pratt’s Figure of Merit index of edge map quality. In almost all test images our algorithm outperforms the standard algorithms in quality and speed.Fil: Nemer, Karim Alejandra. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; ArgentinaFil: Pucheta, Martín Alejo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; ArgentinaFil: Flesia, Ana Georgina. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; ArgentinaTaylor & Francis2016-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/58453Nemer, Karim Alejandra; Pucheta, Martín Alejo; Flesia, Ana Georgina; Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images; Taylor & Francis; Cogent Engineering; 3; 1; 7-2016; 1-212331-1916CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/full/10.1080/23311916.2016.1216725?scroll=top&needAccess=trueinfo:eu-repo/semantics/altIdentifier/doi/10.1080/23311916.2016.1216725info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:40:18Zoai:ri.conicet.gov.ar:11336/58453instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:40:18.338CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images
title Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images
spellingShingle Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images
Nemer, Karim Alejandra
EDGE DETECTION
ENVIRONMENTAL SUSTAINABILITY ENGINEERING
FUZZY LOGIC
SAR IMAGES
WAVELETS
title_short Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images
title_full Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images
title_fullStr Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images
title_full_unstemmed Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images
title_sort Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images
dc.creator.none.fl_str_mv Nemer, Karim Alejandra
Pucheta, Martín Alejo
Flesia, Ana Georgina
author Nemer, Karim Alejandra
author_facet Nemer, Karim Alejandra
Pucheta, Martín Alejo
Flesia, Ana Georgina
author_role author
author2 Pucheta, Martín Alejo
Flesia, Ana Georgina
author2_role author
author
dc.subject.none.fl_str_mv EDGE DETECTION
ENVIRONMENTAL SUSTAINABILITY ENGINEERING
FUZZY LOGIC
SAR IMAGES
WAVELETS
topic EDGE DETECTION
ENVIRONMENTAL SUSTAINABILITY ENGINEERING
FUZZY LOGIC
SAR IMAGES
WAVELETS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The automated detection of coasts, riverbanks, and polynyas from synthetic aperture radar images is a difficult image processing task due to speckle noise. In this work we present a novel Fuzzy-Wavelet framework for bordeline region detection in SAR images. Our technique is based on a combination of Wavelet denoising and Fuzzy Logic which boost decision-making on noisy and poorly defined environments. Unlike most recent filtering-detection algorithms, we do not apply hypothesis tests (Wilcoxon-Mann Whitney-G0) to label the edge point candidates one by one, instead we construct a fuzzy map from wavelet denoised image and extract their borderline. We compare our algorithm performance with the popular Frost-Sobel approach and a version of Canny’s algorithm with data-dependent parameters, over a database of real polynyas and coastline simulated images under the multiplicative model. The experimental results are evaluated by comparing Pratt’s Figure of Merit index of edge map quality. In almost all test images our algorithm outperforms the standard algorithms in quality and speed.
Fil: Nemer, Karim Alejandra. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina
Fil: Pucheta, Martín Alejo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina
Fil: Flesia, Ana Georgina. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina
description The automated detection of coasts, riverbanks, and polynyas from synthetic aperture radar images is a difficult image processing task due to speckle noise. In this work we present a novel Fuzzy-Wavelet framework for bordeline region detection in SAR images. Our technique is based on a combination of Wavelet denoising and Fuzzy Logic which boost decision-making on noisy and poorly defined environments. Unlike most recent filtering-detection algorithms, we do not apply hypothesis tests (Wilcoxon-Mann Whitney-G0) to label the edge point candidates one by one, instead we construct a fuzzy map from wavelet denoised image and extract their borderline. We compare our algorithm performance with the popular Frost-Sobel approach and a version of Canny’s algorithm with data-dependent parameters, over a database of real polynyas and coastline simulated images under the multiplicative model. The experimental results are evaluated by comparing Pratt’s Figure of Merit index of edge map quality. In almost all test images our algorithm outperforms the standard algorithms in quality and speed.
publishDate 2016
dc.date.none.fl_str_mv 2016-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/58453
Nemer, Karim Alejandra; Pucheta, Martín Alejo; Flesia, Ana Georgina; Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images; Taylor & Francis; Cogent Engineering; 3; 1; 7-2016; 1-21
2331-1916
CONICET Digital
CONICET
url http://hdl.handle.net/11336/58453
identifier_str_mv Nemer, Karim Alejandra; Pucheta, Martín Alejo; Flesia, Ana Georgina; Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images; Taylor & Francis; Cogent Engineering; 3; 1; 7-2016; 1-21
2331-1916
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/full/10.1080/23311916.2016.1216725?scroll=top&needAccess=true
info:eu-repo/semantics/altIdentifier/doi/10.1080/23311916.2016.1216725
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844613275200782336
score 13.070432

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