中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Lensless computational imaging technology using deep convolutional network

文献类型:期刊论文

作者Chen, Peidong1,2; Su, Xiuqin1; Liu, Muyuan1,2; Zhu, Wenhua1,2
刊名Sensors (Switzerland)
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
DOI10.3390/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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