Adversarial networks for scale feature-attention spectral image reconstruction from a single RGB
文献类型:期刊论文
作者 | Liu PF(刘鹏飞)1,2,3,4,5; Zhao HC(赵怀慈)1,2,4,5 |
刊名 | SENSORS |
出版日期 | 2020 |
卷号 | 20期号:8页码:1-17 |
ISSN号 | 1424-8220 |
关键词 | hyperspectral imaging generative adversarial network attention mechanism feature pyramid boundary supervision |
产权排序 | 1 |
英文摘要 | Hyperspectral images reconstruction focuses on recovering the spectral information from a single RGBimage. In this paper, we propose two advanced Generative Adversarial Networks (GAN) for the heavily underconstrained inverse problem. We first propose scale attention pyramid UNet (SAPUNet), which uses U-Net with dilated convolution to extract features. We establish the feature pyramid inside the network and use the attention mechanism for feature selection. The superior performance of this model is due to the modern architecture and capturing of spatial semantics. To provide a more accurate solution, we propose another distinct architecture, named W-Net, that builds one more branch compared to U-Net to conduct boundary supervision. SAPUNet and scale attention pyramid WNet (SAPWNet) provide improvements on the Interdisciplinary Computational Vision Lab at Ben Gurion University (ICVL) datasetby 42% and 46.6%, and 45% and 50% in terms of root mean square error (RMSE) and relative RMSE,respectively. The experimental results demonstrate that our proposed models are more accurate than the state-of-the-art hyperspectral recovery methods. |
WOS研究方向 | Chemistry ; Engineering ; Instruments & Instrumentation |
语种 | 英语 |
WOS记录号 | WOS:000533346400268 |
源URL | [http://ir.sia.cn/handle/173321/26747] |
专题 | 沈阳自动化研究所_光电信息技术研究室 |
通讯作者 | Liu PF(刘鹏飞) |
作者单位 | 1.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang 110016, China 2.The Key Lab of Image Understanding and Computer Vision, Shenyang 110016, China 3.University of Chinese Academy of Sciences, Beijing 100049, China 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 5.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
推荐引用方式 GB/T 7714 | Liu PF,Zhao HC. Adversarial networks for scale feature-attention spectral image reconstruction from a single RGB[J]. SENSORS,2020,20(8):1-17. |
APA | Liu PF,&Zhao HC.(2020).Adversarial networks for scale feature-attention spectral image reconstruction from a single RGB.SENSORS,20(8),1-17. |
MLA | Liu PF,et al."Adversarial networks for scale feature-attention spectral image reconstruction from a single RGB".SENSORS 20.8(2020):1-17. |
入库方式: OAI收割
来源:沈阳自动化研究所
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