Paper Info
Title
Hyperspectral And Multispectral Image Fusion Based On Deep Attention Network
Abstract
Hyperspectral (HS) images have rich spectral information and can provide attribute information. High spatial resolution images, such as multispectral (MS) images and panchromatic (PAN) images, can provide fine geometric features. Thus, the fusion of the two images can achieve information complementarity and increase the accuracy and reliability of information. In this paper, we propose a hyperspectral and multispectral image fusion method based on deep attention network. Our model consists of two parts. One is the fusion network, which is used to fuse images. The other part is the spatial attention network, which is used to extract tiny textures and enhance the spatial structure. Experimental results compared with some state-of-the-art methods illustrate that our method is outstanding in both visual and numerical results.
Year
DOI
Venue
2019
10.1109/WHISPERS.2019.8920825
2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
Keywords
DocType
ISSN
Hyperspectral image,multi-spectral image,image fusion,spatial attention,deep learning
Conference
2158-6268
ISBN
Citations 
PageRank 
978-1-7281-5295-0
0
0.34
References 
Authors
7
4
Name
Order
Citations
PageRank
Qing Yang14825.86
Yang Xu271183.57
Zebin Wu387.58
Zhihui Wei442850.68