Dual Branch Autoencoder Network for Spectral-Spatial Hyperspectral Unmixing

Spatial information can play a supporting role in spectral unmixing. In this letter, we propose a dual branch autoencoder network to incorporate spatial-contextual information for spectral-spatial unmixing. The two branches leverage different architectures to efficiently extract spatial information...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5
Hauptverfasser:	Hua, Ziqiang, Li, Xiaorun, Feng, Yueming, Zhao, Liaoying
Format:	Artikel
Sprache:	eng
Schlagworte:	Convergence Convolution Data mining Dual branch autoencoder (DBA) Feature extraction Handicrafts hyperspectral image (HSI) Hyperspectral imaging Image reconstruction Information processing Spatial data Spectra spectral unmixing (SU) spectral-spatial model squared sine distance (SSD) Trigonometric functions Veins
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