Augmented GBM Nonlinear Model to Address Spectral Variability for Hyperspectral Unmixing

Augmented GBM Nonlinear Model to Address Spectral Variability for Hyperspectral Unmixing

Spectral unmixing (SU) is a significant preprocessing task for handling hyperspectral images (HSI), but its process is affected by nonlinearity and spectral variability (SV). Currently, SV is considered within the framework of linear mixing models (LMM), which ignores the nonlinear effects in the sc...

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Bibliographic Details
Main Authors: Linghong Meng, Danfeng Liu, Liguo Wang, Jón Atli Benediktsson, Xiaohan Yue, Yuetao Pan
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Remote Sensing
Subjects:
linear mixing models (LMM)
general bilinear model (GBM)
scaling factors
spectral variability dictionary
alternating direction method of multipliers (ADMM)
Online Access:https://www.mdpi.com/2072-4292/15/12/3205

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https://www.mdpi.com/2072-4292/15/12/3205

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