Least Angle Regression-Based Constrained Sparse Unmixing of Hyperspectral Remote Sensing Imagery

Least Angle Regression-Based Constrained Sparse Unmixing of Hyperspectral Remote Sensing Imagery

Sparse unmixing has been successfully applied in hyperspectral remote sensing imagery analysis based on a standard spectral library known in advance. This approach involves reformulating the traditional linear spectral unmixing problem by finding the optimal subset of signatures in this spectral lib...

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Bibliographic Details
Main Authors: Ruyi Feng, Lizhe Wang, Yanfei Zhong
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Remote Sensing
Subjects:
sparse unmixing
least angle regression
equiangular vector
linear regression
hyperspectral remote sensing imagery
Online Access:http://www.mdpi.com/2072-4292/10/10/1546

Internet

http://www.mdpi.com/2072-4292/10/10/1546

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