Classification of Hyperspectral Images by Gabor Filtering Based Deep Network

In this paper, a novel spectral-spatial classification method based on Gabor filtering and deep network (GFDN) is proposed. First, Gabor features are extracted by performing Gabor filtering on the first three principal components of the hyperspectral image, which can typically characterize the low-l...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing Jg. 11; H. 4; S. 1166 - 1178
Hauptverfasser:	Kang, Xudong, Li, Chengchao, Li, Shutao, Lin, Hui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.04.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Classification Deep learning Feature extraction Gabor filter hyperspectral image (HSI) classification Hyperspectral imaging Image classification Image filters Image reconstruction Machine learning Methods Spatial distribution stacked sparse autoencoders (SSAE) Training virtual samples
ISSN:	1939-1404, 2151-1535
Online-Zugang:	Volltext
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