Lensless computational imaging technology using deep convolutional network
文献类型:期刊论文
作者 | Chen, Peidong1,2; Su, Xiuqin1![]() |
刊名 | Sensors (Switzerland)
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出版日期 | 2020-05-01 |
卷号 | 20期号:9 |
关键词 | lensless lens-free computational imaging deep learning FCN (Fully Convolutional Networks) U-Net Dense-U-Net image reconstruction |
ISSN号 | 14248220 |
DOI | 10.3390/s20092661 |
产权排序 | 1 |
英文摘要 | Within the framework of Internet of Things or when constrained in limited space, lensless imaging technology provides effective imaging solutions with low cost and reduced size prototypes. In this paper, we proposed a method combining deep learning with lensless coded mask imaging technology. After replacing lenses with the coded mask and using the inverse matrix optimization method to reconstruct the original scene images, we applied FCN-8s, U-Net, and our modified version of U-Net, which is called Dense-U-Net, for post-processing of reconstructed images. The proposed approach showed supreme performance compared to the classical method, where a deep convolutional network leads to critical improvements of the quality of reconstruction. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. |
语种 | 英语 |
WOS记录号 | WOS:000537106200225 |
出版者 | MDPI AG, Postfach, Basel, CH-4005, Switzerland |
源URL | [http://ir.opt.ac.cn/handle/181661/93444] ![]() |
专题 | 西安光学精密机械研究所_光电测量技术实验室 |
通讯作者 | Su, Xiuqin |
作者单位 | 1.CAS Key Laboratory of Space Precision Measurement, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an; 710119, China; 2.University of Chinese Academy of Sciences, Beijing; 100049, China |
推荐引用方式 GB/T 7714 | Chen, Peidong,Su, Xiuqin,Liu, Muyuan,et al. Lensless computational imaging technology using deep convolutional network[J]. Sensors (Switzerland),2020,20(9). |
APA | Chen, Peidong,Su, Xiuqin,Liu, Muyuan,&Zhu, Wenhua.(2020).Lensless computational imaging technology using deep convolutional network.Sensors (Switzerland),20(9). |
MLA | Chen, Peidong,et al."Lensless computational imaging technology using deep convolutional network".Sensors (Switzerland) 20.9(2020). |
入库方式: OAI收割
来源:西安光学精密机械研究所
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