Please wait a minute...
Chin. Phys. B, 2020, Vol. 29(2): 024204    DOI: 10.1088/1674-1056/ab671a

Compressed ghost imaging based on differential speckle patterns

Le Wang(王乐)1, Shengmei Zhao(赵生妹)1,2
1 Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunications(NUPT), Nanjing 210003, China;
2 Key Laboratory of Broadband Wireless Communication and Sensor Network Technology(NUPT), Ministry of Education, Nanjing 210003, China
Abstract  We propose a compressed ghost imaging scheme based on differential speckle patterns, named CGI-DSP. In the scheme, a series of bucket detector signals are acquired when a series of random speckle patterns are employed to illuminate an unknown object. Then the differential speckle patterns (differential bucket detector signals) are obtained by taking the difference between present random speckle patterns (present bucket detector signals) and previous random speckle patterns (previous bucket detector signals). Finally, the image of object can be obtained directly by performing the compressed sensing algorithm on the differential speckle patterns and differential bucket detector signals. The experimental and simulated results reveal that CGI-DSP can improve the imaging quality and reduce the number of measurements comparing with the traditional compressed ghost imaging schemes because our scheme can remove the environmental illuminations efficiently.
Keywords:  ghost imaging      compressed sensing      differential speckle patterns      differential bucket detector signals  
Received:  21 October 2019      Revised:  17 November 2019      Accepted manuscript online: 
PACS:  42.30.Va (Image forming and processing)  
  42.30.Wb (Image reconstruction; tomography)  
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 11847062 and 61871234), the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20180755), and the Science Fund from NUPT (Grant No. NY218098).
Corresponding Authors:  Shengmei Zhao     E-mail:

Cite this article: 

Le Wang(王乐), Shengmei Zhao(赵生妹) Compressed ghost imaging based on differential speckle patterns 2020 Chin. Phys. B 29 024204

[1] Strekalov D V, Sergienko A V, Klyshko D N and Shih Y H 1995 Phys. Rev. Lett. 74 3600
[2] Bennink R S, Bentley S J and Boyd R W 2002 Phys. Rev. Lett. 89 113601
[3] Cao D Z, Xu B L, Zhang S H and Wang K G 2015 Chin. Phys. Lett. 32 114208
[4] Li H X, Bai Y F, Shi X H, Nan S Q, Qu L J, Shen Q and Fu X Q 2017 Chin. Phys. B 26 104204
[5] Wang L, Zou L and Zhao S 2018 Opt. Commun. 407 181
[6] Yin M Q, Wang L and Zhao S M 2019 Chin. Phys. B 28 094201
[7] Liu J, Wang J, Chen H, Zheng H, Liu Y, Zhou Y, Li F and Xu Z 2018 Opt. Commun. 410 824
[8] Katz O, Bromberg Y and Silberberg Y 2009 Appl. Phys. Lett. 95 131110
[9] Candés E J, Romberg J K and Tao T 2006 Commun. Pur. Appl. Math. 59 1207
[10] Sun M J, Meng L T, Edgar M P, Padgett M J and Radwell N A 2017 Sci. Rep. 7 3464
[11] Gong W, Zhao C, Yu H, Chen M, Xu W and Han S 2016 Sci. Rep. 6 26133
[12] Zhao S and Zhuang P 2014 Chin. Phys. B 23 054203
[13] Zhao S, Wang L, Liang W, Cheng W and Gong L 2015 Opt. Commun. 353 90
[14] Wang L, Zhao S, Cheng W, Gong L and Chen H 2016 Opt. Commun. 366 314
[15] Yu W K, Yao X R, Liu X F, Li L Z and Zhai G J 2015 Appl. Opt. 54 363
[16] Wang L and Zhao S 2016 Photon. Res. 4 240
[17] Welsh S S, Edgar M P, Bowman R, Sun B and Padgett M J 2015 J. Opt. 17 025705
[18] Li P, Hastie T J and Church K W 2006 Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, August 20-23, 2006, Philadelphia, PA, USA, pp. 287-296
[19] Achlioptas D 2003 J. Comput. Syst. Sci. 66 671
[20] Li C B 2010 An efficient algorithm for total variation regularization with applications to the single pixel camera and compressive sensing (Master Dissertation) (Houston: Rice University)
[1] High speed ghost imaging based on a heuristic algorithm and deep learning
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). Chin. Phys. B, 2021, 30(6): 064202.
[2] Handwritten digit recognition based on ghost imaging with deep learning
Xing He(何行), Sheng-Mei Zhao(赵生妹), and Le Wang(王乐). Chin. Phys. B, 2021, 30(5): 054201.
[3] Identification of denatured and normal biological tissues based on compressed sensing and refined composite multi-scale fuzzy entropy during high intensity focused ultrasound treatment
Shang-Qu Yan(颜上取), Han Zhang(张含), Bei Liu(刘备), Hao Tang(汤昊), and Sheng-You Qian(钱盛友). Chin. Phys. B, 2021, 30(2): 028704.
[4] Compressive imaging based on multi-scale modulation and reconstruction in spatial frequency domain
Fan Liu(刘璠), Xue-Feng Liu(刘雪峰), Ruo-Ming Lan(蓝若明), Xu-Ri Yao(姚旭日), Shen-Cheng Dou(窦申成), Xiao-Qing Wang(王小庆), and Guang-Jie Zhai(翟光杰). Chin. Phys. B, 2021, 30(1): 014208.
[5] An image compressed sensing algorithm based on adaptive nonlinear network
Yuan Guo(郭媛), Wei Chen(陈炜), Shi-Wei Jing(敬世伟). Chin. Phys. B, 2020, 29(5): 054203.
[6] Super-resolution filtered ghost imaging with compressed sensing
Shao-Ying Meng(孟少英), Wei-Wei Shi(史伟伟), Jie Ji(季杰), Jun-Jie Tao(陶俊杰), Qian Fu(付强), Xi-Hao Chen(陈希浩), and Ling-An Wu(吴令安). Chin. Phys. B, 2020, 29(12): 128704.
[7] Experimental demonstration of influence of underwater turbulence on ghost imaging
Man-Qian Yin(殷曼倩), Le Wang(王乐), Sheng-Mei Zhao(赵生妹). Chin. Phys. B, 2019, 28(9): 094201.
[8] Mask-based denoising scheme for ghost imaging
Yang Zhou(周阳), Shu-Xu Guo(郭树旭), Fei Zhong(钟菲), Tian Zhang(张天). Chin. Phys. B, 2019, 28(8): 084204.
[9] Enhancement of spatial resolution of ghost imaging via localizing and thresholding
Yunlong Wang(王云龙), Yingnan Zhou(周英男), Shaoxiong Wang(王少雄), Feiran Wang(王斐然), Ruifeng Liu(刘瑞丰), Hong Gao(高宏), Pei Zhang(张沛), Fuli Li(李福利). Chin. Phys. B, 2019, 28(4): 044202.
[10] Influence of random phase modulation on the imaging quality of computational ghost imaging
Chao Gao(高超), Xiao-Qian Wang(王晓茜), Hong-Ji Cai(蔡宏吉), Jie Ren(任捷), Ji-Yuan Liu(刘籍元), Zhi-Hai Yao(姚治海). Chin. Phys. B, 2019, 28(2): 020201.
[11] Ghost images reconstructed from fractional-order moments with thermal light
De-Zhong Cao(曹德忠), Qing-Chen Li(李清晨), Xu-Cai Zhuang(庄绪财), Cheng Ren(任承), Su-Heng Zhang(张素恒), Xin-Bing Song(宋新兵). Chin. Phys. B, 2018, 27(12): 123401.
[12] Visibility enhancement in two-dimensional lensless ghost imaging with true thermal light
Xi-Hao Chen(陈希浩), Ling Yan(燕玲), Wei Wu(吴炜), Shao-Ying Meng(孟少英), Ling-An Wu(吴令安), Zhi-Bin Sun(孙志斌), Chao Wang(王超), Guang-Jie Zhai(翟光杰). Chin. Phys. B, 2017, 26(6): 060702.
[13] Optical encryption scheme based on ghost imaging with disordered speckles
Yu-dong Zhang(张玉东), Sheng-mei Zhao(赵生妹). Chin. Phys. B, 2017, 26(5): 054205.
[14] Reflective ghost imaging free from vibrating detectors
Heng-xing Li(李恒星), Yan-feng Bai(白艳锋), Xiao-hui Shi(施晓辉), Su-qin Nan(南苏琴), Li-jie Qu(屈利杰), Qian Shen(沈倩), Xi-quan Fu(傅喜泉). Chin. Phys. B, 2017, 26(10): 104204.
[15] Compressed sensing sparse reconstruction for coherent field imaging
Bei Cao(曹蓓), Xiu-Juan Luo(罗秀娟), Yu Zhang(张羽), Hui Liu(刘 辉), Ming-Lai Chen(陈明徕). Chin. Phys. B, 2016, 25(4): 040701.
No Suggested Reading articles found!