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Article: Noise effect on linear spectral unmixing

TitleNoise effect on linear spectral unmixing
Authors
Issue Date1999
Citation
Geographic Information Sciences, 1999, v. 5, n. 1, p. 52-57 How to Cite?
AbstractUsing hyperspectral reflectance data collected from six types of surface covers, we synthesized linear mixtures and used them to test the sensitivity of two linear unmixing algorithms to simulated additive noise. We found both algorithms were highly sensitive to noise. This may considerably limit their use in remote sensing. © 1999 Taylor & Francis Group, LLC.
Persistent Identifierhttp://hdl.handle.net/10722/296926
ISSN

 

DC FieldValueLanguage
dc.contributor.authorGong, P.-
dc.contributor.authorZhang, A.-
dc.date.accessioned2021-02-25T15:16:59Z-
dc.date.available2021-02-25T15:16:59Z-
dc.date.issued1999-
dc.identifier.citationGeographic Information Sciences, 1999, v. 5, n. 1, p. 52-57-
dc.identifier.issn1082-4006-
dc.identifier.urihttp://hdl.handle.net/10722/296926-
dc.description.abstractUsing hyperspectral reflectance data collected from six types of surface covers, we synthesized linear mixtures and used them to test the sensitivity of two linear unmixing algorithms to simulated additive noise. We found both algorithms were highly sensitive to noise. This may considerably limit their use in remote sensing. © 1999 Taylor & Francis Group, LLC.-
dc.languageeng-
dc.relation.ispartofGeographic Information Sciences-
dc.titleNoise effect on linear spectral unmixing-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/10824009909480514-
dc.identifier.scopuseid_2-s2.0-0038054805-
dc.identifier.volume5-
dc.identifier.issue1-
dc.identifier.spage52-
dc.identifier.epage57-
dc.identifier.issnl1082-4006-

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