Unsupervised hyperspectral band selection by combination of unmixing and sequential clustering techniques

Unsupervised hyperspectral band selection by combination of unmixing and sequential clustering techniques

Selecting the decisive spectral bands is a key issue in unsupervised hyperspectral band selection techniques. These methods are the most popular ways for dimensionality reduction of original data. A compact data representation without compromising the physical information and optimizing the separati...

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Bibliographic Details
Main Authors:	Sarra Ikram Benabadji, Moussa Sofiane Karoui, Khelifa Djerriri, Issam Boukerch, Nezha Farhi, Mohammed Amine Bouhlala
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2019-01-01
Series:	European Journal of Remote Sensing
Subjects:	hyperspectral imagery dimensionality reduction unsupervised band selection linear spectral unmixing sequential clustering
Online Access:	http://dx.doi.org/10.1080/22797254.2018.1549511

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