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dc.contributor.author
Nemer, Karim Alejandra
dc.contributor.author
Pucheta, Martín Alejo
dc.contributor.author
Flesia, Ana Georgina
dc.date.available
2018-09-05T20:28:09Z
dc.date.issued
2016-07
dc.identifier.citation
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
dc.identifier.issn
2331-1916
dc.identifier.uri
http://hdl.handle.net/11336/58453
dc.description.abstract
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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Taylor & Francis
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Edge Detection
dc.subject
Environmental Sustainability Engineering
dc.subject
Fuzzy Logic
dc.subject
Sar Images
dc.subject
Wavelets
dc.subject.classification
Ciencias de la Computación
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Unsupervised fuzzy-wavelet framework for coastal polynya detection in synthetic aperture radar images
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-09-05T16:10:06Z
dc.journal.volume
3
dc.journal.number
1
dc.journal.pagination
1-21
dc.journal.pais
Reino Unido
dc.journal.ciudad
Londres
dc.description.fil
Fil: Nemer, Karim Alejandra. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina
dc.description.fil
Fil: Pucheta, Martín Alejo. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina
dc.description.fil
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
dc.journal.title
Cogent Engineering
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/full/10.1080/23311916.2016.1216725?scroll=top&needAccess=true
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1080/23311916.2016.1216725
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