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Deblurring and Sparse Unmixing for Hyperspectral Images

Author
ZHAO, Xi-Le1 ; FAN WANG2 ; HUANG, Ting-Zhu1 ; NG, Michael K3 ; PLEMMONS, Robert J4
[1] School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China
[2] Department of Mathematics and Statistics, Lanzhou University, Lanzhou, China
[3] Centre for Mathematical Imaging and Vision and the Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong-Kong
[4] Department of Computer Science and the Department of Mathematics, Wake Forest University, Winston-Salem, NC 27106, United States
Source

IEEE transactions on geoscience and remote sensing. 2013, Vol 51, Num 7, pp 4045-4058, 14 p ; 1 ; ref : 39 ref

CODEN
IGRSD2
ISSN
0196-2892
Scientific domain
Agronomy, agriculture, phytopathology; Ecology; Geology; Geophysics; Telecommunications
Publisher
Institute of Electrical and Electronics Engineers, New York, NY
Publication country
United States
Document type
Article
Language
English
Author keyword
Alternating direction methods deblurring hyperspectral imaging linear spectral unmixing total variation (TV)
Keyword (fr)
Efficacité Imagerie Modèle Optimisation Traitement image Télédétection Imagerie hyperspectrale
Keyword (en)
efficiency imagery models optimization image processing remote sensing
Keyword (es)
Imaginería Modelo Optimización Detección a distancia
Classification
Pascal
001 Exact sciences and technology / 001E Earth, ocean, space / 001E01 Earth sciences / 001E01M Internal geophysics / 001E01M04 Applied geophysics

Discipline
Earth sciences
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
27530133

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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