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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Vydané v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 11; číslo 4; s. 1166 - 1178
Hlavní autori:	Kang, Xudong, Li, Chengchao, Li, Shutao, Lin, Hui
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.04.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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