Hyperspectral Unmixing via Low-Rank Representation with Space Consistency Constraint and Spectral Library Pruning

Hyperspectral Unmixing via Low-Rank Representation with Space Consistency Constraint and Spectral Library Pruning

Spectral unmixing is a popular technique for hyperspectral data interpretation. It focuses on estimating the abundance of pure spectral signature (called as endmembers) in each observed image signature. However, the identification of the endmembers in the original hyperspectral data becomes a challe...

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Bibliographic Details
Main Authors: Xiangrong Zhang, Chen Li, Jingyan Zhang, Qimeng Chen, Jie Feng, Licheng Jiao, Huiyu Zhou
Format: Article
Language:English
Published: MDPI AG 2018-02-01
Series:Remote Sensing
Subjects:
hyperspectral remote sensing
spectral unmixing
space consistency constraint
dictionary pruning
Online Access:http://www.mdpi.com/2072-4292/10/2/339

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