Endmember Estimation from Hyperspectral Images Using Geometric Distances

Literals

bibo:issn
- 1545-598X
ou:tipoPublicacion
- Article
fabio:hasPublicationYear
- 2022
dcterms:publisher
- IEEE Geoscience and Remote Sensing Letters
ou:eid
- 2-s2.0-85122394517
ou:bibtex
- @article{Paoletti2022,title = {Endmember Estimation from Hyperspectral Images Using Geometric Distances},journal = {IEEE Geoscience and Remote Sensing Letters},year = {2022},volume = {19},author = {Tao, X. and Paoletti, M.E. and Haut, J.M. and Han, L. and Ren, P. and Plaza, J. and Plaza, A.}}
dcterms:contributor
- Tao X.; Paoletti M.E.; Haut J.M.; Han L.; Ren P.; Plaza J.; Plaza A.
bibo:eissn
- 1558-0571
vivo:identifier
- 2022-256
dcterms:creator
- Tao X.
bibo:doi
- 10.1109/lgrs.2021.3102076
dcterms:title
- Endmember Estimation from Hyperspectral Images Using Geometric Distances
vcard:url
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85122394517&origin=inward
ou:urlOrcid
- http://www.scopus.com/inward/record.url?eid=2-s2.0-85122394517&partnerID=MN8TOARS
ou:urlScopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85122394517&origin=inward
bibo:volume
- 19