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A Remote Security Computational Ghost Imaging Method Based on Quantum Key Distribution Technology

delete2022-01-01
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OA
AI
J
Jianan Wu
Y
Yun Chen
C
Cheng Zhou
Z
Zhongyang Chen
C
Chengqian Xu
L
Lijun Song *
DOI:10.1109/ACCESS.2022.3144297delete
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摘要

摘要

En 中文
Computational ghost imaging (CGI) is a method of acquiring object information by measuring light field intensity, which would be used to achieve imaging in a complicated environment. The main issue to be addressed in CGI technology is how to achieve rapid and high-quality imaging while assuring the secure transmission of detection data in practical distant imaging applications. In order to address the mentioned issues, this paper proposes a remote secure CGI method based on quantum communication technology. Using the quantum key distribution (QKD) network, the CGI system can be reconstructed while solving the problem of information security transmission between the detector and the reconstructed computing device. By exploring the influence of different random measurement matrices on the quality of image reconstruction, it is found that the randomness of the numerical sequence constituting the matrix is positively correlated with the imaging quality. Based on this discovery, a new type of quantum cryptography measurement matrix is constructed using quantum cryptography with good randomness. In addition, through further orthogonalization and normalization of the matrix, the matrix has both good randomness and orthogonality, and high-quality imaging results can be obtained at a low sampling rate. The feasibility and effectiveness of the method are verified by simulation imaging experiments. Compared with the traditional GI system, the method proposed in this paper has higher transmission security and high-quality imaging under this premise, which provides a new idea for the practical development of CGI technology.
Keyword:
Computational ghost imaging
quantum key distribution
quantum cryptography
measurement matrix
randomness
schimidt orthogonalization

期刊

IEEE Access 封面图
IEEE Access
IF:
3.6
论文数:
9.8W
被引数:
29.4W

机构

C
Changchun University
学者数:
1.7K
论文数: 824
被引数: 1.4K
N
northeast normal university - china
学者数:
1.2W
论文数: 9.2K
被引数: 23
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