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Alternative TitleHyperspectral images reconstruction using adversarial networks from single RGB image
刘鹏飞1,2,3,4,5; 赵怀慈1,2,4,5; 李培玄1,2,3,4,5
Source Publication红外与激光工程
Indexed ByEI
EI Accession number20203609139677
Contribution Rank1
Funding Organization装备预研重点基金(JZX7Y2019025049301)
Keyword高光谱成像 特征金字塔 生成对抗网络 注意力机制


Other Abstract

Hyperspectral imaging can provide more spectral information than an ordinary RGB camera. The spectral information has been beneficial to numerous applications, such as monitoring natural environment changes and classifying plants and soils in agriculture. The hyperspectral images reconstruction from a single RGB image is severely unconstrained problem. Previous methods need additional components or the spectral response by commercial camera. An end-to-end conditional generative adversarial network was proposed with modified residual network as backbone. The feature pyramid was used inside the network and a scale attention module was designed to fuse local and global information. In order to provide more accurate solution, another distinct architecture was proposed, named WNet. Experiments manifested the superiority of the proposed method over other representative methods in terms of quality and quantity. Experiments used both synthesized RGB images using public hyperspectral data and real-world image by ordinary camera demonstrate that proposed method outperforms the state-of-the-art. The WNet drops 45% and 50% in terms of RMSE and relative RMSE on the ICVL dataset than sparse coding. © 2020, Editorial Board of Journal of Infrared and Laser Engineering. All right reserved.

Document Type期刊论文
Corresponding Author赵怀慈
Recommended Citation
GB/T 7714
刘鹏飞,赵怀慈,李培玄. 对抗网络实现单幅RGB重建高光谱图像[J]. 红外与激光工程,2020,49(S1):1-8.
APA 刘鹏飞,赵怀慈,&李培玄.(2020).对抗网络实现单幅RGB重建高光谱图像.红外与激光工程,49(S1),1-8.
MLA 刘鹏飞,et al."对抗网络实现单幅RGB重建高光谱图像".红外与激光工程 49.S1(2020):1-8.
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