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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Bibliographic Details
Published in:	IEEE geoscience and remote sensing letters Vol. 19; pp. 1 - 5
Main Authors:	Hua, Ziqiang, Li, Xiaorun, Feng, Yueming, Zhao, Liaoying
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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
ISSN:	1545-598X, 1558-0571
Online Access:	Get full text
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