Hyperspectral Band Selection With Iterative Graph Autoencoder

Hyperspectral band selection (BS) is an important task for hyperspectral image (HSI) processing, which aims to select a discriminative and low-redundant band subset. As a significant cue for BS, structure information describes the cross-band correlation, which brings the redundancy of HSI. Existing...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing Jg. 61; S. 1 - 13
Hauptverfasser:	Zhou, Yuan, Yao, Qingren, Huo, Shuwei, Li, Xiaofeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Banded structure Construction Convolution Correlation Design Feature extraction Graph autoencoder (GAE) Graph neural networks graph representation Graphical representations hyperspectral band selection (BS) Hyperspectral imaging Information processing Iterative methods Methods Neural networks Redundancy representativeness Symmetric matrices Task analysis
ISSN:	0196-2892, 1558-0644
Online-Zugang:	Volltext
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