DAMS: Dilated Attention with Multi-Stream Learning for Super-Resolution of Hyperspectral Remote Sensing Images

Hyperspectral super-resolution (SR) can effectively enhance the spatial resolution of hyperspectral images, holding significant application value. Nevertheless, existing methods tend to overlook global information and some detailed aspects of hyperspectral images, resulting in limitations in feature...

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Vydané v:	IEEE International Geoscience and Remote Sensing Symposium proceedings s. 8995 - 8998
Hlavní autori:	Li, Sheng, Xu, Ruoqing, Su, Yuanchao, Gao, Lianru, Sun, Xu, Ren, Longfei, Zhu, Zhiqing
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 07.07.2024
Predmet:	Autoencoder Convolutional neural networks Dams Deep Leaning Feature extraction Hyperspectral imaging Hyperspectral Remote Sensing Spatial resolution super-resolution Superresolution
ISSN:	2153-7003
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