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Multiple-image Encryption and Multiplexing Using a Modified Gerchberg-Saxton Algorithm in Fresnel-transform Domain and Computational Ghost Imaging

  • Peiming Zhang (School of Health Science and Engineering, University of Shanghai for Science and Technology) ;
  • Yahui Su (College of Communication and Art Design, University of Shanghai for Science and Technology) ;
  • Yiqiang Zhang (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology) ;
  • Leihong Zhang (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology) ;
  • Runchu Xu (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology) ;
  • Kaimin Wang (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology) ;
  • Dawei Zhang (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology)
  • Received : 2023.03.22
  • Accepted : 2023.06.06
  • Published : 2023.08.25

Abstract

Optical information processing technology is characterized by high speed and parallelism, and the light features short wavelength and large information capacity; At the same time, it has various attributes including amplitude, phase, wavelength and polarization, and is a carrier of multi-dimensional information. Therefore, optical encryption is of great significance in the field of information security transmission, and is widely used in the field of image encryption. For multi-image encryption, this paper proposes a multi-image encryption algorithm based on a modified Gerchberg-Saxton algorithm (MGSA) in the Fresnel-transform domain and computational ghost imaging. First, MGSA is used to realize "one code, one key"; Second, phase function superposition and normalization are used to reduce the amount of ciphertext transmission; Finally, computational ghost imaging is used to improve the security of the whole encryption system. This method can encrypt multiple images simultaneously with high efficiency, simple calculation, safety and reliability, and less data transmission. The encryption effect of the method is evaluated by using correlation coefficient and structural similarity, and the effectiveness and security of the method are verified by simulation experiments.

Keywords

Acknowledgement

National Natural Science Foundation of China (No. 62275153, 62005165); Shanghai Industrial Collaborative Innovation Project (HCXBCY-2022-006).

References

  1. O. Matoba, T. Nomura, E. Perez-Cabre, M. S. Millan, and B. Javidi, "Optical techniques for information security," IEEE Access 97, 1128-1148 (2009). 
  2. D. Xiao, X. Li, S.-J. Liu, and Q.-H. Wang, "Encryption and display of multiple-image information using computer generated holography with modified GS iterative algorithm," Opt. Commun. 410, 488-495 (2018).  https://doi.org/10.1016/j.optcom.2017.09.087
  3. Y. Kang, L. Zhang, H. Ye, M. Zhao, S. Kanwal, C. Bai, and D. Zhang, "One-to-many optical information encryption transmission method based on temporal ghost imaging and code division multiple access," Photonics Res. 7, 1370-1380 (2019).  https://doi.org/10.1364/PRJ.7.001370
  4. X. Li, M. Zhao, Y. Xing, H.-L. Zhang, L. Li, S.-T. Kim, X. Zhou, and Q.-H. Wang, "Designing optical 3D images encryption and reconstruction using monospectral synthetic aperture integral imaging," Opt. Express 26, 11084-11099 (2018).  https://doi.org/10.1364/OE.26.011084
  5. W. Chen, B. Javidi, and X. Chen, "Advances in optical security systems," Adv. Opt. Photonics 6, 120-155 (2014).  https://doi.org/10.1364/AOP.6.000120
  6. Y. Shi, T. Li, Y. Wang, Q. Gao, S. G. Zhang, and H. Li, "Optical image encryption via ptychography," Opt. Express 38, 1425-1427 (2013). 
  7. Z. Liu, Q. Guo, L. Xu, M. A. Ahmad, and S. Liu, "Double image encryption by using iterative random binary encoding in gyrator domains," Opt. Express 18, 12033-12043 (2010).  https://doi.org/10.1364/OE.18.012033
  8. W. Qin and X. Peng, "Asymmetric cryptosystem based on phase-truncated Fourier transforms," Opt. Express 35, 118-120 (2010). 
  9. X. C. Cheng, L. Z. Cai, Y. R. Wang, X. F. Meng, H. Zhang, X. F. Xu, X. X. Shen, and G. Y. Dong, "Security enhancement of double random phase encryption by amplitude modulation," Opt. Lett. 33, 1575-1577 (2008).  https://doi.org/10.1364/OL.33.001575
  10. P. Kumar, A. Kumar, J. Joseph, and K. Singh, "Impulse attack free double random phase encryption scheme with randomized lens-phase functions," Opt. Lett. 34, 331-333 (2009).  https://doi.org/10.1364/OL.34.000331
  11. P. Kumar, J. Joseph, and K. Simgh, "Impulse attack free four random phase mask encryption based on a 4-f optical system," Appl. Opt. 48, 2356-2363 (2009).  https://doi.org/10.1364/AO.48.002356
  12. G. Situ and J. Zhang, "Double random-phase encoding in the Fresnel domain," Opt. Lett. 29, 1584-1586 (2004).  https://doi.org/10.1364/OL.29.001584
  13. Y. Yang, B. Guan, J. Li, D. Li, Y.-H. Zhou, and W.-M. Shi, "Image compression-encryption scheme based on fractional order hyperchaotic system combined with 2D compressed sensing and DNA encoding," Opt. Laser Technol. 119, 105666 (2019). 
  14. L. Huang, H. Liu, and Z. Y. Wang, "Self-adaptive image encryption algorithm combining chaotic map with DNA computing," J. Chin. Comput. Syst. 41, 1959-1965 (2020). 
  15. H. Zhang, X.-Q. Wang, Y.-J. Su, and X.-Y. Wang, "A novel method for lossless image compression and encryption based on LWT, SPIHT and cellular automata," Signal Process Image Commun. 84, 115829 (2020). 
  16. N. Zhou, H. Li, D. Wang, S. Pan, and Z. Zhou, "Image compression and encryption scheme based on 2D compressive sensing and fractional Mellin transform," Opt. Commun. 343, 10-21 (2015).  https://doi.org/10.1016/j.optcom.2014.12.084
  17. X. Chai, X. Fu, Z. Gan, Y. Lu, and Y. Chen, "A color image cryptosystem based on dynamic DNA encryption and chaos," Signal Process 155, 44-62 (2019).  https://doi.org/10.1016/j.sigpro.2018.09.029
  18. X. Wang and S. Gao, "Image encryption algorithm for synchronously updating Boolean networks based on matrix semi-tensor product theory," Inf. Sci. 507, 16-36 (2020).  https://doi.org/10.1016/j.ins.2019.08.041
  19. L. Zhu, H. Song, and X. L. Zhang, "A novel image encryption scheme based on nonuniform sampling in block con pressive sensing," IEEE Access 7, 22161-22174 (2019).  https://doi.org/10.1109/ACCESS.2019.2897721
  20. L. H. Zhang, Z. L. Pan, and G. L. Zhou, "Study on the key technology of optical encryption based on adaptive compressive ghost imaging for a large-sized object," J. Opt. Technol. 84, 471-476 (2017).  https://doi.org/10.1364/JOT.84.000471
  21. O. Katz, Y. Bromberg, and Y. Silberberg, "Compressive ghost imaging," Appl. Phys. Lett. 95, 131110 (2009). 
  22. C. Li, C. Gao, J. Q. Shao, X. Q. Wang, and Z. Yao, "Hadamard ghost imaging based on compressed sensing reconstruction algorithm," Laser Photonics Rev. 58, 1011032 (2021). 
  23. X. Li, X. Meng, X. Yang, Y. Yin, Y. Wang, X. Peng, W. He, G. Dong, and H. Chen, "Multiple-image encryption based on compressive ghost imaging and coordinate sampling," IEEE Photonics J. 8, 3900511 (2016). 
  24. X. Li, X. Meng, X. Yang, Y. Wang, Y. Yin, X. Peng, W. He, G. Dong, and H. Chen, "Multiple-image encryption via lifting wavelet transform and XOR operation based on compressive ghost imaging scheme," Opt. Lasers Eng. 102, 106-111 (2018).  https://doi.org/10.1016/j.optlaseng.2017.10.023
  25. J. Wu, Z. Xie, Z. Liu, W. Liu, Y. Zhang, and S. Liu, "Multiple-image encryption based on computational ghost imaging," Opt. Commun. 359, 38-43 (2016).  https://doi.org/10.1016/j.optcom.2015.09.039
  26. L. Zhang, Z. Zhang, H. Ye, Y. Kang, Z. Wang, K. Wang, and D. Zhang, "Multi-image holographic encryption based on phase recovery algorithm and ghost imaging," Appl. Phys. B 126, 136-142 (2020). 
  27. L. Sui, X. Zhao, C. Huang, A. Tian, and A. Anand, "An optical multiple-image authentication based on transport of intensity equation," Opt. Lasers Eng. 116, 116-124 (2019).  https://doi.org/10.1016/j.optlaseng.2019.01.006
  28. X. Zhai, Z.-D. Cheng, Y.-D. Hu, Y. Chen, Z.-Y. Liang, and Y. Wei, "Foveated ghost imaging based on deep learning," Opt. Commun. 448, 69-75 (2019).  https://doi.org/10.1016/j.optcom.2019.05.019
  29. R. C. Gonzalez and P. Wintz, "Digital Image Processing," IEEE Trans. Pattern Anal. Mach. Intell. 3, 242-243 (1981). 
  30. X. Mei, C. Wang, Y. Fang, T. Song, W. Gong, and S. Han, "Influence of the source's energy fluctuation on computational ghost imaging and effective correction approaches," Chin. Opt. Lett. 18, 042602 (2020). 
  31. H.-E. Hwang, H. T. Chang, and W.-N. Lie, "Multiple-image encryption and multiplexing using a modified Gerchberg-Saxton algorithm and phase modulation in Fresnel-transform domain," Opt. Lett. 34, 3917-3919 (2009). https://doi.org/10.1364/OL.34.003917