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Phase retrieval based on difference map and deep neural networks
Li, Baopeng1,2,3,4; Ersoy, Okan K.4; Ma, Caiwen1; Pan, Zhibin2; Wen, Wansha1,3; Song, Zongxi1; Gao, Wei1
Department空间光学技术研究室
Source PublicationJournal of Modern Optics
ISSN09500340;13623044
Contribution Rank1
Abstract

Phase retrieval occurs in many research areas. There are some classical phase retrieval methods such as hybrid input-output (HIO) and difference map (DM). However, phase retrieval results are sensitive to noise, and the reconstructed images always include artefacts. In this paper, we use the DM algorithm together with DNN to get better phase retrieval results. We train one deep neural network using amplitude images and phase images, respectively. First, using DM, we get initial reconstructed amplitude and phase results. Then, using DNN improves both amplitude and phase results. Finally, using the DM algorithm again improves the DNN results further. The numerical experimental results show that using DM gives better results than HIO, and using DNN improves phase information better than just using DNN to train for amplitude information alone. Compared with only using DNN improves amplitude methods, our method using DM plus DNN plus DM yields a better reconstruction performance for both amplitude and phase. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

KeywordPhase retrieval difference map deep neural network U-net coherent diffractive imaging
DOI10.1080/09500340.2021.1977860
Indexed BySCI ; EI
Language英语
WOS IDWOS:000697200100001
PublisherTaylor and Francis Ltd.
EI Accession Number20213810923757
Citation statistics
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/95082
Collection空间光学技术研究室
Corresponding AuthorWen, Wansha
Affiliation1.Xi'an, Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China;
2.Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China;
3.University of Chinese Academy of Sciences, Beijing, China;
4.School of Electrical and Computer Engineering, Purdue University, West Lafayette; IN, United States
Recommended Citation
GB/T 7714
Li, Baopeng,Ersoy, Okan K.,Ma, Caiwen,et al. Phase retrieval based on difference map and deep neural networks[J]. Journal of Modern Optics.
APA Li, Baopeng.,Ersoy, Okan K..,Ma, Caiwen.,Pan, Zhibin.,Wen, Wansha.,...&Gao, Wei.
MLA Li, Baopeng,et al."Phase retrieval based on difference map and deep neural networks".Journal of Modern Optics
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