Sparsity-Constrained Coupled Nonnegative Matrix–Tensor Factorization for Hyperspectral Unmixing

Sparsity-Constrained Coupled Nonnegative Matrix–Tensor Factorization for Hyperspectral Unmixing

Hyperspectral unmixing refers to a source separation problem of decomposing a hyperspectral imagery (HSI) to estimate endmembers, and their corresponding abundances. Recently, matrix-vector nonnegative tensor factorization (MV-NTF) was proposed for unmixing to avoid structure information loss, which...

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Bibliographic Details
Main Authors: Heng-Chao Li, Shuang Liu, Xin-Ru Feng, Shao-Quan Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Coupled decomposition
hyperspectral unmixing
nonnegative matrix factorization (NMF)
nonnegative tensor factorization (NTF)
sparsity constraint
Online Access:https://ieeexplore.ieee.org/document/9178427/

Internet

https://ieeexplore.ieee.org/document/9178427/

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