NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORM

Detalhes bibliográficos
Autor(a) principal: XU, DONG
Data de Publicação: 2013
Outros Autores: SUN, LEI, LUO, JIANSHU
Tipo de documento: Artigo
Idioma: por
Título da fonte: Boletim de Ciências Geodésicas
Texto Completo: https://revistas.ufpr.br/bcg/article/view/34878
Resumo: Noise estimation of hyperspectral remote sensing image is important for itspost-processing and application. In this paper, not only the spectral correlationremoving is considered, but the spatial correlation removing by wavelet transform isconsidered as well. Therefore, a new method based on multiple linear regression(MLR) and wavelet transform is proposed to estimate the noise of hyperspectralremote sensing image. Numerical simulation of AVIRIS data is carried out and thereal data Hyperion is also used to validate the proposed algorithm. Experimentalresults show that the method is more adaptive and accurate than the general MLRand the other classified methods.
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network_name_str Boletim de Ciências Geodésicas
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spelling NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORMGeociências; GeodésiaGeodésiaNoise estimation of hyperspectral remote sensing image is important for itspost-processing and application. In this paper, not only the spectral correlationremoving is considered, but the spatial correlation removing by wavelet transform isconsidered as well. Therefore, a new method based on multiple linear regression(MLR) and wavelet transform is proposed to estimate the noise of hyperspectralremote sensing image. Numerical simulation of AVIRIS data is carried out and thereal data Hyperion is also used to validate the proposed algorithm. Experimentalresults show that the method is more adaptive and accurate than the general MLRand the other classified methods.Boletim de Ciências GeodésicasBulletin of Geodetic SciencesNational Natural Science Foundation of ChinaXU, DONGSUN, LEILUO, JIANSHU2013-12-20info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufpr.br/bcg/article/view/34878Boletim de Ciências Geodésicas; Vol 19, No 4 (2013)Bulletin of Geodetic Sciences; Vol 19, No 4 (2013)1982-21701413-4853reponame:Boletim de Ciências Geodésicasinstname:Universidade Federal do Paraná (UFPR)instacron:UFPRporhttps://revistas.ufpr.br/bcg/article/view/34878/21646info:eu-repo/semantics/openAccess2013-12-20T20:16:14Zoai:revistas.ufpr.br:article/34878Revistahttps://revistas.ufpr.br/bcgPUBhttps://revistas.ufpr.br/bcg/oaiqdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br1982-21701413-4853opendoar:2013-12-20T20:16:14Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR)false
dc.title.none.fl_str_mv NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORM
title NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORM
spellingShingle NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORM
XU, DONG
Geociências; Geodésia
Geodésia
title_short NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORM
title_full NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORM
title_fullStr NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORM
title_full_unstemmed NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORM
title_sort NOISE ESTIMATION OF HYPERSPECTRAL REMOTE SENSING IMAGE BASED ON MULTIPLE LINEAR REGRESSION AND WAVELET TRANSFORM
author XU, DONG
author_facet XU, DONG
SUN, LEI
LUO, JIANSHU
author_role author
author2 SUN, LEI
LUO, JIANSHU
author2_role author
author
dc.contributor.none.fl_str_mv National Natural Science Foundation of China
dc.contributor.author.fl_str_mv XU, DONG
SUN, LEI
LUO, JIANSHU
dc.subject.por.fl_str_mv Geociências; Geodésia
Geodésia
topic Geociências; Geodésia
Geodésia
description Noise estimation of hyperspectral remote sensing image is important for itspost-processing and application. In this paper, not only the spectral correlationremoving is considered, but the spatial correlation removing by wavelet transform isconsidered as well. Therefore, a new method based on multiple linear regression(MLR) and wavelet transform is proposed to estimate the noise of hyperspectralremote sensing image. Numerical simulation of AVIRIS data is carried out and thereal data Hyperion is also used to validate the proposed algorithm. Experimentalresults show that the method is more adaptive and accurate than the general MLRand the other classified methods.
publishDate 2013
dc.date.none.fl_str_mv 2013-12-20
dc.type.none.fl_str_mv

dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revistas.ufpr.br/bcg/article/view/34878
url https://revistas.ufpr.br/bcg/article/view/34878
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://revistas.ufpr.br/bcg/article/view/34878/21646
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Boletim de Ciências Geodésicas
Bulletin of Geodetic Sciences
publisher.none.fl_str_mv Boletim de Ciências Geodésicas
Bulletin of Geodetic Sciences
dc.source.none.fl_str_mv Boletim de Ciências Geodésicas; Vol 19, No 4 (2013)
Bulletin of Geodetic Sciences; Vol 19, No 4 (2013)
1982-2170
1413-4853
reponame:Boletim de Ciências Geodésicas
instname:Universidade Federal do Paraná (UFPR)
instacron:UFPR
instname_str Universidade Federal do Paraná (UFPR)
instacron_str UFPR
institution UFPR
reponame_str Boletim de Ciências Geodésicas
collection Boletim de Ciências Geodésicas
repository.name.fl_str_mv Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR)
repository.mail.fl_str_mv qdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br
_version_ 1799771722641047552

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