Sparse and Low-Rank Constrained Tensor Factorization for Hyperspectral Image Unmixing

Sparse and Low-Rank Constrained Tensor Factorization for Hyperspectral Image Unmixing

Third-order tensors have been widely used in hyperspectral remote sensing because of their ability to maintain the 3-D structure of hyperspectral images. In recent years, hyperspectral unmixing algorithms based on tensor factorization have emerged, but these decomposition processes may be inconsiste...

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Bibliographic Details
Main Authors: Pan Zheng, Hongjun Su, Qian Du
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Hyperspectral remote sensing
low-rank
sparse
tensor factorization
unmixing
Online Access:https://ieeexplore.ieee.org/document/9312393/

Internet

https://ieeexplore.ieee.org/document/9312393/

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