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所属单位：计算机学院

刊物所在地：USA

关键字：Feedback embedding, hyperspectral image (HSI), pixel awareness, recurrent network, super-resolution

摘要：Hyperspectral images (HSIs) contain abundant spec tral information, while the spatial resolution is usually limited. To obtain high-spatial-resolution HSIs, various HSI super-resolution (SR) methods are proposed. Currently, deep-learning-based SR reconstruction methods are studied in depth, which take different measures to make full use of the spatial and spectral information of HSIs, and optimize the network with lots of trainings. Although they have achieved satisfying spatial resolution, the spectral con sistency before and after reconstruction is difficult to guarantee. In this article, we

合写作者：Ruyi Feng, Zhongyu Guo and Xiaofeng Wang*

论文类型：期刊论文

通讯作者：Xiaofeng Wang

学科门类：工学

一级学科：计算机

文献类型：J

是否译文：否

收录刊物：EI