Optical image compression and encryption transmission-based ondeep learning and ghost imaging

被引:10
作者
Zhang, Leihong [1 ]
Xiong, Rui [1 ]
Chen, Jian [2 ]
Zhang, Dawei [3 ]
机构
[1] Univ Shanghai Sci & Technol, Coll Commun & Art Design, Shanghai 200093, Peoples R China
[2] Hefei ZC Optoelect Technol Ltd, Anhui Prov Key Lab Nondestruct Evaluat, Hefei 230000, Anhui, Peoples R China
[3] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai 200093, Peoples R China
来源
APPLIED PHYSICS B-LASERS AND OPTICS | 2020年 / 126卷 / 01期
基金
美国国家科学基金会; 上海市自然科学基金;
关键词
JPEG;
D O I
10.1007/s00340-019-7362-1
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This paper proposes an optical image compression and encryption transmission based on deep learning and ghost imaging, which uses ghost imaging as a point-to-face transmission mode to reduce the influence of chaotic medium and turbulence on the communication channel, and combine with the deep learning to improve the reconstructed image resolution. In this method, first, the image is preprocessed by JPEG to obtain a compressed image, and the compressed image is transmitted as an image to be transmitted, which can improve the transmission rate; then, the ghost imaging is used for transmission, which can improve the anti-interference ability and transmission security of the transmission; finally, the problem of poor image quality after ghost-imaging transmission, using deep learning for reconstruction, which can improve the resolution of the image. In the simulation experiment, feasibility analysis, safety analysis, and robustness analysis were carried out, respectively, and the experimental results were objectively evaluated using correlation methods such as peak signal-to-noise ratio, mutual information, and histogram. The experimental results show that the proposed method can provide a feasible and secure optical communication image transmission method and realize high-resolution transmission image reconstruction, which has guiding significance for optical communication.
引用
收藏
页数:10
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