Efficient implementation of x-ray ghost imaging based on a modified compressive sensing algorithm

doi:10.1088/1674-1056/ac48f7

中国物理B ›› 2022, Vol. 31 ›› Issue (6): 64202-064202.doi: 10.1088/1674-1056/ac48f7

Efficient implementation of x-ray ghost imaging based on a modified compressive sensing algorithm

Haipeng Zhang(张海鹏)^1,2,3, Ke Li(李可)², Changzhe Zhao(赵昌哲)^1,2,3, Jie Tang(汤杰), and Tiqiao Xiao(肖体乔)^1,2,3,†

1 Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China;
2 Shanghai Synchrotron Radiation Facility/Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201204, China;
3 University of Chinese Academy of Sciences, Beijing 100049, China

收稿日期:2021-09-22 修回日期:2022-01-02 接受日期:2022-01-07 出版日期:2022-05-17 发布日期:2022-05-19
通讯作者: Tiqiao Xiao E-mail:xiaotiqiao@zjlab.org.cn
基金资助:
Project supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA0206004,2017YFA0206002, 2018YFC0206002, and 2017YFA0403801) and National Natural Science Foundation of China (Grant No. 81430087).

Efficient implementation of x-ray ghost imaging based on a modified compressive sensing algorithm

Haipeng Zhang(张海鹏)^1,2,3, Ke Li(李可)², Changzhe Zhao(赵昌哲)^1,2,3, Jie Tang(汤杰), and Tiqiao Xiao(肖体乔)^1,2,3,†

1 Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China;
2 Shanghai Synchrotron Radiation Facility/Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201204, China;
3 University of Chinese Academy of Sciences, Beijing 100049, China

Received:2021-09-22 Revised:2022-01-02 Accepted:2022-01-07 Online:2022-05-17 Published:2022-05-19
Contact: Tiqiao Xiao E-mail:xiaotiqiao@zjlab.org.cn
Supported by:
Project supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA0206004,2017YFA0206002, 2018YFC0206002, and 2017YFA0403801) and National Natural Science Foundation of China (Grant No. 81430087).

摘要/Abstract

摘要： Towards efficient implementation of x-ray ghost imaging (XGI), efficient data acquisition and fast image reconstruction together with high image quality are preferred. In view of radiation dose resulted from the incident x-rays, fewer measurements with sufficient signal-to-noise ratio (SNR) are always anticipated. Available methods based on linear and compressive sensing algorithms cannot meet all the requirements simultaneously. In this paper, a method based on a modified compressive sensing algorithm with conjugate gradient descent method (CGDGI) is developed to solve the problems encountered in available XGI methods. Simulation and experiments demonstrate the practicability of CGDGI-based method for the efficient implementation of XGI. The image reconstruction time of sub-second implicates that the proposed method has the potential for real-time XGI.

关键词: x-ray ghost imaging, modified compressive sensing algorithm, real-time x-ray imaging

Abstract: Towards efficient implementation of x-ray ghost imaging (XGI), efficient data acquisition and fast image reconstruction together with high image quality are preferred. In view of radiation dose resulted from the incident x-rays, fewer measurements with sufficient signal-to-noise ratio (SNR) are always anticipated. Available methods based on linear and compressive sensing algorithms cannot meet all the requirements simultaneously. In this paper, a method based on a modified compressive sensing algorithm with conjugate gradient descent method (CGDGI) is developed to solve the problems encountered in available XGI methods. Simulation and experiments demonstrate the practicability of CGDGI-based method for the efficient implementation of XGI. The image reconstruction time of sub-second implicates that the proposed method has the potential for real-time XGI.

Key words: x-ray ghost imaging, modified compressive sensing algorithm, real-time x-ray imaging

中图分类号: (Image forming and processing)

42.30.Va

42.30.Wb (Image reconstruction; tomography)

Haipeng Zhang(张海鹏), Ke Li(李可), Changzhe Zhao(赵昌哲), Jie Tang(汤杰), and Tiqiao Xiao(肖体乔). Efficient implementation of x-ray ghost imaging based on a modified compressive sensing algorithm[J]. 中国物理B, 2022, 31(6): 64202-064202.

参考文献

[1] Ferri F, Magatti D, Gatti A, Bache M, Brambilla E and Lugiato L A 2005 Phys. Rev. Lett. 94 183062
[2] Yu H, Lu R H, Han S S, Xie H L, Du G H, Xiao T Q and Zhu D M 2016 Phys. Rev. Lett. 117 113901
[3] Huang Y Y, Ouyang C, Fang K, Dong Y F, Zhang J, Chen L M and Wu L A 2021 Chin. Phys. B 30 064202
[4] Gatti A, Brambilla E, Bache M and Lugiato L A 2004 Phys. Rev. Lett. 93 093602
[5] Zhang M H, Wei Q, Shen X, Liu Y F, Liu H L, Chen J and Han S S 2007 Phys. Rev. A 75 021803
[6] Chen X H, Liu Q, Luo K H and Wu L A 2009 Opt. Lett. 34 695
[7] Chen X H, Agafonov I N, Luo K H, Liu Q, Xian R, Chekhova M V and Wu L A 2010 Opt. Lett. 35 1166
[8] Gong W L 2015 Photon. Res. 3 234
[9] Meng S Y, Shi W W, Ji J, Tao J J, Fu Q, Chen X H and Wu L A 2020 Chin. Phys. B 29 128704
[10] Oh J E, Cho Y W, Scarcelli G and Kim Y H 2013 Opt. Lett. 38 682
[11] Kingston A M, Fullagar W K, Myers G R, Adams D, Pelliccia D and Paganin D M 2021 Phys. Rev. A 103 033503
[12] Zhang A X, He Y H, Wu L A, Chen L M and Wang B B 2018 Optica 5 374
[13] Pelliccia D, Rack A, Schell M, Cantelli V and Paganin D M 2016 Phys. Rev. Lett. 117 113902
[14] Schori A and Shwartz S. 2017 Opt. Express 25 14822
[15] Kingston A M, Pelliccia D, Rack A, Olbinado M P, Cheng Y, Myers G R and Paganin D M 2018 Optica 5 1516
[16] Wang L and Zhao S M 2020 Chin. Phys. B 29 024204
[17] Li E R, Chen M L, Gong W L, Wang H and Han S S 2012 Journal of Electronics (China) 29 617
[18] Rizvi S, Cao J, Zhang K Y and Hao Q 2020 Scientific Reports 10 11400
[19] Li Q, Duan Z T, Lin H Z, Gao S B, Sun S and Liu W T 2016 Chin. Opt. Lett. 14 111103
[20] Klein Y, Schori A, Dolbnya I P, Sawhney K and Shwartz S 2019 Opt. Express 27 3284
[21] Katz O, Bromberg Y and Siberberg Y 2009 Appl. Phys. Lett. 95 131110
[22] Zhao S M and Zhuang P 2014 Chin. Phys. B 23 054203
[23] Ferri F, Magatti D, Lugiato L A and Gatti A 2010 Phys. Rev. Lett. 104 253603
[24] Li C 2011 An efficient algorithm for total variation regularization with applications to the single pixel camera and compressive sensing (Ph. D. dissertation) (Huston: Rice University)
[25] Wang J, Kwon S, Li P and Shim B 2016 IEEE Transactions on Signal Processing 64 1076
[26] Chen S S, Donoho D L and Saunders M A 1998 SIAM J. Sci. Comput. 20 33
[27] Martino D, Matias Flores J, Ayubi J L, Alonso G A, Fernandez J R, Ferrari A and Jose A 2012 Appl. Opt. 51 3439
[28] Wang Z, Bovik A C, Sheikh H R and Simoncelli E P 2004 Transactions on Image Processing (IEEE) 13 600
[29] Tang W J 2015 Research on Compressed Sensing Reconstruction Algorithm and Its Application in Wireless Sensor Networks (MS dissertation) (Nanjing: Nanjing University of Posts and telecommunications) (in Chinese)
[30] Yao X R, Yu W K, Liu X F, Li L Z, Li M F, Wu L A and Zhai G J 2014 Opt. Express 22 24268
[31] Zhang C, Guo S X, Cao J S, Guan J and Gao F L 2014 Opt. Express 22 30063
[32] Pelliccia D, Olbinado M, Rack A, Kingston A, Myers G and Paganin D M 2018 IUCrJ 5 428
[33] Gao C, Wang X Q, Cai H J, Ren J, Liu J Y and Yao Z H 2019 Chin. Phys. B 28 20201

Efficient implementation of x-ray ghost imaging based on a modified compressive sensing algorithm

Efficient implementation of x-ray ghost imaging based on a modified compressive sensing algorithm

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