Efficient Two-Phase Multiobjective Sparse Unmixing Approach for Hyperspectral Data

Efficient Two-Phase Multiobjective Sparse Unmixing Approach for Hyperspectral Data

In our previous work, a two-phase multiobjective sparse unmixing (Tp-MoSU) approach has been proposed, which settled the regularization parameter issues of the regularization unmixing methods. However, Tp-MoSU has limited performance in identifying the real end-members from the highly noisy data in...

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Bibliographic Details
Main Authors: Xiangming Jiang, Maoguo Gong, Tao Zhan, Kai Sheng, Mingliang Xu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Composite spectral similarity measure
highly noisy data
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multiobjective sparse unmixing
spatial-contextual information
time efficiency
Online Access:https://ieeexplore.ieee.org/document/9337884/

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https://ieeexplore.ieee.org/document/9337884/

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