期刊
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 14, 期 5, 页码 639-643出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2017.2668299
关键词
Convolutional neural networks (CNNs); deep learning (DL); hyperspectral (HS); image fusion; multispectral (MS)
类别
资金
- Icelandic Research Fund [174075-05]
- University of Iceland Research Fund
In this letter, we propose a method using a 3-D convolutional neural network to fuse together multispectral and hyperspectral (HS) images to obtain a high resolution HS image. Dimensionality reduction of the HS image is performed prior to fusion in order to significantly reduce the computational time and make the method more robust to noise. Experiments are performed on a data set simulated using a real HS image. The results obtained show that the proposed approach is very promising when compared with conventional methods. This is especially true when the HS image is corrupted by additive noise.
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