Super-resolution border segmentation and measurement in remote sensing images

Autores
Cipolletti, Marina Paola; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Piccolo, Maria Cintia
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Segmentation and measurement of linear characteristics in remote sensing imagery are among the first stages in several geomorphologic studies, including the length estimation of geographic features such as perimeters, coastal lines, and borders. However, unlike area measurement algorithms, widely used methods for perimeter estimation in digital images have high systematic errors. No precision improvement can be achieved with finer spatial resolution images because of the inherent geometrical inaccuracies they commit. In this work, a superresolution border segmentation and measurement algorithm is presented. The method is based on minimum distance segmentation over the initial image, followed by contour tracking using a superresolution enhancement of the marching squares algorithm. Thorough testing with synthetic and validated field images shows that this algorithm outperforms traditional border measuring methods, regardless of the image resolution or the orientation, size, and shape of the object to be analyzed.
Fil: Cipolletti, Marina Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina
Fil: Delrieux, Claudio Augusto. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Laboratorio de Sistemas Digitales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentina
Fil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina
Fil: Piccolo, Maria Cintia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina
Materia
Segmentation
Measurement
Perimeter
Superresolution
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:11336/269080
Acceder
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spelling Super-resolution border segmentation and measurement in remote sensing imagesCipolletti, Marina PaolaDelrieux, Claudio AugustoPerillo, Gerardo Miguel E.Piccolo, Maria CintiaSegmentationMeasurementPerimeterSuperresolutionhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Segmentation and measurement of linear characteristics in remote sensing imagery are among the first stages in several geomorphologic studies, including the length estimation of geographic features such as perimeters, coastal lines, and borders. However, unlike area measurement algorithms, widely used methods for perimeter estimation in digital images have high systematic errors. No precision improvement can be achieved with finer spatial resolution images because of the inherent geometrical inaccuracies they commit. In this work, a superresolution border segmentation and measurement algorithm is presented. The method is based on minimum distance segmentation over the initial image, followed by contour tracking using a superresolution enhancement of the marching squares algorithm. Thorough testing with synthetic and validated field images shows that this algorithm outperforms traditional border measuring methods, regardless of the image resolution or the orientation, size, and shape of the object to be analyzed.Fil: Cipolletti, Marina Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Delrieux, Claudio Augusto. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Laboratorio de Sistemas Digitales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Piccolo, Maria Cintia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaPergamon-Elsevier Science Ltd2012-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/269080Cipolletti, Marina Paola; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Piccolo, Maria Cintia; Super-resolution border segmentation and measurement in remote sensing images; Pergamon-Elsevier Science Ltd; Computers & Geosciences; 40; 3-2012; 87-960098-3004CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0098300411002548info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cageo.2011.07.015info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:54:32Zoai:ri.conicet.gov.ar:11336/269080instacron: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:34982025-09-03 09:54:32.565CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Super-resolution border segmentation and measurement in remote sensing images
title Super-resolution border segmentation and measurement in remote sensing images
spellingShingle Super-resolution border segmentation and measurement in remote sensing images
Cipolletti, Marina Paola
Segmentation
Measurement
Perimeter
Superresolution
title_short Super-resolution border segmentation and measurement in remote sensing images
title_full Super-resolution border segmentation and measurement in remote sensing images
title_fullStr Super-resolution border segmentation and measurement in remote sensing images
title_full_unstemmed Super-resolution border segmentation and measurement in remote sensing images
title_sort Super-resolution border segmentation and measurement in remote sensing images
dc.creator.none.fl_str_mv Cipolletti, Marina Paola
Delrieux, Claudio Augusto
Perillo, Gerardo Miguel E.
Piccolo, Maria Cintia
author Cipolletti, Marina Paola
author_facet Cipolletti, Marina Paola
Delrieux, Claudio Augusto
Perillo, Gerardo Miguel E.
Piccolo, Maria Cintia
author_role author
author2 Delrieux, Claudio Augusto
Perillo, Gerardo Miguel E.
Piccolo, Maria Cintia
author2_role author
author
author
dc.subject.none.fl_str_mv Segmentation
Measurement
Perimeter
Superresolution
topic Segmentation
Measurement
Perimeter
Superresolution
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Segmentation and measurement of linear characteristics in remote sensing imagery are among the first stages in several geomorphologic studies, including the length estimation of geographic features such as perimeters, coastal lines, and borders. However, unlike area measurement algorithms, widely used methods for perimeter estimation in digital images have high systematic errors. No precision improvement can be achieved with finer spatial resolution images because of the inherent geometrical inaccuracies they commit. In this work, a superresolution border segmentation and measurement algorithm is presented. The method is based on minimum distance segmentation over the initial image, followed by contour tracking using a superresolution enhancement of the marching squares algorithm. Thorough testing with synthetic and validated field images shows that this algorithm outperforms traditional border measuring methods, regardless of the image resolution or the orientation, size, and shape of the object to be analyzed.
Fil: Cipolletti, Marina Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina
Fil: Delrieux, Claudio Augusto. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Laboratorio de Sistemas Digitales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentina
Fil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina
Fil: Piccolo, Maria Cintia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina
description Segmentation and measurement of linear characteristics in remote sensing imagery are among the first stages in several geomorphologic studies, including the length estimation of geographic features such as perimeters, coastal lines, and borders. However, unlike area measurement algorithms, widely used methods for perimeter estimation in digital images have high systematic errors. No precision improvement can be achieved with finer spatial resolution images because of the inherent geometrical inaccuracies they commit. In this work, a superresolution border segmentation and measurement algorithm is presented. The method is based on minimum distance segmentation over the initial image, followed by contour tracking using a superresolution enhancement of the marching squares algorithm. Thorough testing with synthetic and validated field images shows that this algorithm outperforms traditional border measuring methods, regardless of the image resolution or the orientation, size, and shape of the object to be analyzed.
publishDate 2012
dc.date.none.fl_str_mv 2012-03
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/11336/269080
Cipolletti, Marina Paola; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Piccolo, Maria Cintia; Super-resolution border segmentation and measurement in remote sensing images; Pergamon-Elsevier Science Ltd; Computers & Geosciences; 40; 3-2012; 87-96
0098-3004
CONICET Digital
CONICET
url http://hdl.handle.net/11336/269080
identifier_str_mv Cipolletti, Marina Paola; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Piccolo, Maria Cintia; Super-resolution border segmentation and measurement in remote sensing images; Pergamon-Elsevier Science Ltd; Computers & Geosciences; 40; 3-2012; 87-96
0098-3004
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0098300411002548
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cageo.2011.07.015
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
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
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
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score 13.13397

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