Target Detection With Unconstrained Linear Mixture Model and Hierarchical Denoising Autoencoder in Hyperspectral Imagery

Hyperspectral imagery with very high spectral resolution provides a new insight for subtle nuances identification of similar substances. However, hyperspectral target detection faces significant challenges of intraclass dissimilarity and interclass similarity due to the unavoidable interference caus...

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Veröffentlicht in:	IEEE transactions on image processing Jg. 31; S. 1418 - 1432
Hauptverfasser:	Li, Yunsong, Shi, Yanzi, Wang, Keyan, Xi, Bobo, Li, Jiaojiao, Gamba, Paolo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Deep learning Detectors Forecasting hierarchical denoising autoencoder Hyperspectral imaging hyperspectral target detection Interference Mixture models Noise reduction Object detection Probabilistic models spatial-spectral unification Spectra Spectral resolution Target detection Unconstrained linear mixture model
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
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