PMGMCN: A Parallel Dynamic Multihop Graph and Composite Multiscale Convolution Network for Hyperspectral Sparse Unmixing

In recent years, sparse unmixing (SU) has garnered significant attention in hyperspectral images (HSI) because it does not require endmember estimation, relying instead on prior spectral libraries to represent observed HSI data, which avoids the influence of endmember extraction on unmixing. However...

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Bibliographic Details

Published in:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Main Authors:	Kewen Qu, Huiyang Wang, Mingming Ding, Xiaojuan Luo, Fangzhou Luo
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	Adaptive weighted total variation (TV) loss function CNN-GCN composite multiscale convolution dynamic multihop graph sparse unmixing (SU)
Online Access:	https://ieeexplore.ieee.org/document/10937499/