Uncertainty Estimation by Convolution Using Spatial Statistics

Kriging has proven to be a useful tool in image processing since it behaves, under regular sampling, as a convolution. Convolution kernels obtained with kriging allow noise filtering and include the effects of the random fluctuations of the experimental data and the resolution of the measuring devic...

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Detalles Bibliográficos
Autores: Sánchez Brea, Luis Miguel, Bernabeu Martínez, Eusebio
Tipo de recurso: artículo
Fecha de publicación:2006
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/51193
Acceso en línea:https://hdl.handle.net/20.500.14352/51193
Access Level:acceso abierto
Palabra clave:535
Sampling Theorem
Noisy Images
Shannon
Óptica (Física)
2209.19 Óptica Física
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oai_identifier_str oai:docta.ucm.es:20.500.14352/51193
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spelling Uncertainty Estimation by Convolution Using Spatial StatisticsSánchez Brea, Luis MiguelBernabeu Martínez, Eusebio535Sampling TheoremNoisy ImagesShannonÓptica (Física)2209.19 Óptica FísicaKriging has proven to be a useful tool in image processing since it behaves, under regular sampling, as a convolution. Convolution kernels obtained with kriging allow noise filtering and include the effects of the random fluctuations of the experimental data and the resolution of the measuring devices. The uncertainty at each location of the image can also be determined using kriging. However, this procedure is slow since, currently, only matrix methods are available. In this work, we compare the way kriging performs the uncertainty estimation with the standard statistical technique for magnitudes without spatial dependence. As a result, we propose a much faster technique, based on the variogram, to determine the uncertainty using a convolutional procedure. We check the validity of this approach by applying it to one-dimensional images obtained in diffractometry and two-dimensional images obtained by shadow moire.IEEE Institute of Electrical and Electronics EngineersUniversidad Complutense de Madrid20062006-10-0120062006-10-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/51193reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/511932026-06-02T12:44:21Z
dc.title.none.fl_str_mv Uncertainty Estimation by Convolution Using Spatial Statistics
title Uncertainty Estimation by Convolution Using Spatial Statistics
spellingShingle Uncertainty Estimation by Convolution Using Spatial Statistics
Sánchez Brea, Luis Miguel
535
Sampling Theorem
Noisy Images
Shannon
Óptica (Física)
2209.19 Óptica Física
title_short Uncertainty Estimation by Convolution Using Spatial Statistics
title_full Uncertainty Estimation by Convolution Using Spatial Statistics
title_fullStr Uncertainty Estimation by Convolution Using Spatial Statistics
title_full_unstemmed Uncertainty Estimation by Convolution Using Spatial Statistics
title_sort Uncertainty Estimation by Convolution Using Spatial Statistics
dc.creator.none.fl_str_mv Sánchez Brea, Luis Miguel
Bernabeu Martínez, Eusebio
author Sánchez Brea, Luis Miguel
author_facet Sánchez Brea, Luis Miguel
Bernabeu Martínez, Eusebio
author_role author
author2 Bernabeu Martínez, Eusebio
author2_role author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 535
Sampling Theorem
Noisy Images
Shannon
Óptica (Física)
2209.19 Óptica Física
topic 535
Sampling Theorem
Noisy Images
Shannon
Óptica (Física)
2209.19 Óptica Física
description Kriging has proven to be a useful tool in image processing since it behaves, under regular sampling, as a convolution. Convolution kernels obtained with kriging allow noise filtering and include the effects of the random fluctuations of the experimental data and the resolution of the measuring devices. The uncertainty at each location of the image can also be determined using kriging. However, this procedure is slow since, currently, only matrix methods are available. In this work, we compare the way kriging performs the uncertainty estimation with the standard statistical technique for magnitudes without spatial dependence. As a result, we propose a much faster technique, based on the variogram, to determine the uncertainty using a convolutional procedure. We check the validity of this approach by applying it to one-dimensional images obtained in diffractometry and two-dimensional images obtained by shadow moire.
publishDate 2006
dc.date.none.fl_str_mv 2006
2006-10-01
2006
2006-10-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/51193
url https://hdl.handle.net/20.500.14352/51193
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv IEEE Institute of Electrical and Electronics Engineers
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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