Object Reconstruction Using the Binomial Theorem for Ghost Imaging
Noise term in the reconstruction matrix in ghost imaging is a major cause of blurring imaging results. To remedy this problem, we propose a new ghost imaging method based on the binomial theorem to reduce the level of noise. In our method, images with low-level noise can be generated by constructing...
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Photonics Journal |
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| Online Access: | https://ieeexplore.ieee.org/document/8528411/ |
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| author | Cong Yue Ping Chen Xiaofeng Lv Chenglong Wang Shuxu Guo Junfeng Song Wenlin Gong Fengli Gao |
| author_facet | Cong Yue Ping Chen Xiaofeng Lv Chenglong Wang Shuxu Guo Junfeng Song Wenlin Gong Fengli Gao |
| author_sort | Cong Yue |
| collection | DOAJ |
| description | Noise term in the reconstruction matrix in ghost imaging is a major cause of blurring imaging results. To remedy this problem, we propose a new ghost imaging method based on the binomial theorem to reduce the level of noise. In our method, images with low-level noise can be generated by constructing a binomial formula using high-order imaging results that are acquired by reintroducing the reconstruction result back into the imaging formula repeatedly. Experimental and simulation results demonstrate that our method is effective in improving imaging quality and the anti-interference performance and reducing computing time, making it useful for practical applications. |
| format | Article |
| id | doaj-art-c30f5e6e9a67487b9f4dcc836c8ba6cf |
| institution | Kabale University |
| issn | 1943-0655 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-c30f5e6e9a67487b9f4dcc836c8ba6cf2025-08-20T03:32:37ZengIEEEIEEE Photonics Journal1943-06552018-01-0110611310.1109/JPHOT.2018.28804308528411Object Reconstruction Using the Binomial Theorem for Ghost ImagingCong Yue0Ping Chen1Xiaofeng Lv2https://orcid.org/0000-0003-0975-2201Chenglong Wang3https://orcid.org/0000-0002-4617-0182Shuxu Guo4Junfeng Song5Wenlin Gong6Fengli Gao7https://orcid.org/0000-0003-0975-2201State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, ChinaState Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, ChinaState Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, ChinaKey Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, ChinaState Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, ChinaState Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, ChinaKey Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, ChinaState Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, ChinaNoise term in the reconstruction matrix in ghost imaging is a major cause of blurring imaging results. To remedy this problem, we propose a new ghost imaging method based on the binomial theorem to reduce the level of noise. In our method, images with low-level noise can be generated by constructing a binomial formula using high-order imaging results that are acquired by reintroducing the reconstruction result back into the imaging formula repeatedly. Experimental and simulation results demonstrate that our method is effective in improving imaging quality and the anti-interference performance and reducing computing time, making it useful for practical applications.https://ieeexplore.ieee.org/document/8528411/Imaging processingcoherence imagingphoton statisticsquantum optics |
| spellingShingle | Cong Yue Ping Chen Xiaofeng Lv Chenglong Wang Shuxu Guo Junfeng Song Wenlin Gong Fengli Gao Object Reconstruction Using the Binomial Theorem for Ghost Imaging IEEE Photonics Journal Imaging processing coherence imaging photon statistics quantum optics |
| title | Object Reconstruction Using the Binomial Theorem for Ghost Imaging |
| title_full | Object Reconstruction Using the Binomial Theorem for Ghost Imaging |
| title_fullStr | Object Reconstruction Using the Binomial Theorem for Ghost Imaging |
| title_full_unstemmed | Object Reconstruction Using the Binomial Theorem for Ghost Imaging |
| title_short | Object Reconstruction Using the Binomial Theorem for Ghost Imaging |
| title_sort | object reconstruction using the binomial theorem for ghost imaging |
| topic | Imaging processing coherence imaging photon statistics quantum optics |
| url | https://ieeexplore.ieee.org/document/8528411/ |
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