High speed ghost imaging based on a heuristic algorithm and deep learning

doi:10.1088/1674-1056/abea8c

中国物理B ›› 2021, Vol. 30 ›› Issue (6): 64202-064202.doi: 10.1088/1674-1056/abea8c

High speed ghost imaging based on a heuristic algorithm and deep learning

Yi-Yi Huang(黄祎祎)^1,2, Chen Ou-Yang(欧阳琛)^1,2, Ke Fang(方可)^1,2, Yu-Feng Dong(董玉峰)¹, Jie Zhang(张杰)^1,3, Li-Ming Chen(陈黎明)^3,4,†, and Ling-An Wu(吴令安)^1,2,‡

1 Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China;
2 University of Chinese Academy of Sciences, Beijing 100049, China;
3 IFSA Collaborative Innovation Center and School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, China;
4 College of Engineering Physics, Shenzhen Technology University, Shenzhen 518118, China

收稿日期:2020-12-17 修回日期:2021-02-10 接受日期:2021-03-01 出版日期:2021-05-18 发布日期:2021-06-05
通讯作者: Li-Ming Chen, Ling-An Wu E-mail:lmchen@sjtu.edu.cn;wula@iphy.ac.cn
基金资助:
Project supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA0403301, 2017YFB0503301, and 2018YFB0504302), the National Natural Science Foundation of China (Grant Nos. 11991073, 61975229, and Y8JC011L51), the Key Program of CAS (Grant No. XDB17030500), the Civil Space Project (Grant No. D040301), and the Science Challenge Project (Grant No. TZ2018005).

High speed ghost imaging based on a heuristic algorithm and deep learning

Yi-Yi Huang(黄祎祎)^1,2, Chen Ou-Yang(欧阳琛)^1,2, Ke Fang(方可)^1,2, Yu-Feng Dong(董玉峰)¹, Jie Zhang(张杰)^1,3, Li-Ming Chen(陈黎明)^3,4,†, and Ling-An Wu(吴令安)^1,2,‡

1 Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China;
2 University of Chinese Academy of Sciences, Beijing 100049, China;
3 IFSA Collaborative Innovation Center and School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, China;
4 College of Engineering Physics, Shenzhen Technology University, Shenzhen 518118, China

Received:2020-12-17 Revised:2021-02-10 Accepted:2021-03-01 Online:2021-05-18 Published:2021-06-05
Contact: Li-Ming Chen, Ling-An Wu E-mail:lmchen@sjtu.edu.cn;wula@iphy.ac.cn
Supported by:
Project supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA0403301, 2017YFB0503301, and 2018YFB0504302), the National Natural Science Foundation of China (Grant Nos. 11991073, 61975229, and Y8JC011L51), the Key Program of CAS (Grant No. XDB17030500), the Civil Space Project (Grant No. D040301), and the Science Challenge Project (Grant No. TZ2018005).

摘要/Abstract

摘要： We report an overlapping sampling scheme to accelerate computational ghost imaging for imaging moving targets, based on reordering a set of Hadamard modulation matrices by means of a heuristic algorithm. The new condensed overlapped matrices are then designed to shorten and optimize encoding of the overlapped patterns, which are shown to be much superior to the random matrices. In addition, we apply deep learning to image the target, and use the signal acquired by the bucket detector and corresponding real image to train the neural network. Detailed comparisons show that our new method can improve the imaging speed by as much as an order of magnitude, and improve the image quality as well.

关键词: high speed computational ghost imaging, heuristic algorithm, deep learning

Abstract: We report an overlapping sampling scheme to accelerate computational ghost imaging for imaging moving targets, based on reordering a set of Hadamard modulation matrices by means of a heuristic algorithm. The new condensed overlapped matrices are then designed to shorten and optimize encoding of the overlapped patterns, which are shown to be much superior to the random matrices. In addition, we apply deep learning to image the target, and use the signal acquired by the bucket detector and corresponding real image to train the neural network. Detailed comparisons show that our new method can improve the imaging speed by as much as an order of magnitude, and improve the image quality as well.

Key words: high speed computational ghost imaging, heuristic algorithm, deep learning

中图分类号: (Imaging and optical processing)

42.30.-d

42.30.Va (Image forming and processing) 42.30.Wb (Image reconstruction; tomography)

Yi-Yi Huang(黄祎祎), Chen Ou-Yang(欧阳琛), Ke Fang(方可), Yu-Feng Dong(董玉峰), Jie Zhang(张杰), Li-Ming Chen(陈黎明), and Ling-An Wu(吴令安). High speed ghost imaging based on a heuristic algorithm and deep learning[J]. 中国物理B, 2021, 30(6): 64202-064202.

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High speed ghost imaging based on a heuristic algorithm and deep learning

High speed ghost imaging based on a heuristic algorithm and deep learning

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