[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Springer Nature Link
Log in

Adaptive LSB quantum watermarking method using tri-way pixel value differencing

  • Published:
Quantum Information Processing Aims and scope Submit manuscript

Abstract

As an important way to protect copyright by embedding watermark in digital images, quantum watermarking catches more and more attentions. In this study, a novel quantum watermarking method on the basis of tri-way pixel value differencing and modified least significant bit (LSB) substitution is proposed. A quantum cover image using the novel-enhanced quantum image representation is partitioned into non-overlapping 2 × 2 blocks with four pixels firstly. To classify the block as a smooth area or an edge area, the tri-way pixel value differences are calculated and compared with a predefined threshold. The quantum watermark image, which is expanded and scrambled, is then embedded into a quantum cover image by the k-bit LSB substitution method, where k is decided by the level of each block. The embedded quantum watermark can be extracted from the quantum stego-image without the assistance of original quantum cover image. Theoretical analysis and simulation-based experiments demonstrate both the feasibility and capabilities of the proposed quantum watermarking method, which has good visual quality, better robustness, and higher security.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Le, P.Q., Dong, F., Hirota, K.: A flexible representation of quantum images for polynomial preparation, image compression, and processing operations. Quantum Inf. Process. 10, 63–84 (2011). https://doi.org/10.1007/s11128-010-0177-y

    Article  MathSciNet  MATH  Google Scholar 

  2. Zhang, Y., Lu, K., Gao, Y., Wang, M.: NEQR: a novel enhanced quantum representation of digital images. Quantum Inf. Process. 12, 2833–2860 (2013). https://doi.org/10.1007/s11128-013-0567-z

    Article  ADS  MathSciNet  MATH  Google Scholar 

  3. Li, H.-S., Zhu, Q., Li, M., Ian, H.: Multidimensional color image storage, retrieval, and compression based on quantum amplitudes and phases. Inf. Sci. (Ny). 273, 212–232 (2014). https://doi.org/10.1016/j.ins.2014.03.035

    Article  Google Scholar 

  4. Zhang, Y., Lu, K., Xu, K., Gao, Y., Wilson, R.: Local feature point extraction for quantum images. Quantum Inf. Process. 14, 1573–1588 (2015). https://doi.org/10.1007/s11128-014-0842-7

    Article  ADS  MathSciNet  MATH  Google Scholar 

  5. Jiang, N., Wang, L.: Quantum image scaling using nearest neighbor interpolation. Quantum Inf. Process. 14, 1559–1571 (2015). https://doi.org/10.1007/s11128-014-0841-8

    Article  ADS  MathSciNet  MATH  Google Scholar 

  6. Zhou, R.-G., Hu, W., Fan, P., Ian, H.: Quantum realization of the bilinear interpolation method for NEQR. Sci. Rep. 7, 2511 (2017). https://doi.org/10.1038/s41598-017-02575-6

    Article  ADS  Google Scholar 

  7. Yang, Y.G., Zhao, Q.Q., Sun, S.J.: Novel quantum gray-scale image matching. Optik (Stuttg) 126, 3340–3343 (2015). https://doi.org/10.1016/j.ijleo.2015.08.010

    Article  ADS  Google Scholar 

  8. Jiang, N., Dang, Y., Wang, J.: Quantum image matching. Quantum Inf. Process. 15, 3543–3572 (2016). https://doi.org/10.1007/s11128-016-1364-2

    Article  ADS  MathSciNet  MATH  Google Scholar 

  9. Luo, G., Zhou, R., Liu, X.: Fuzzy matching based on gray-scale difference for quantum images. Int. J. Theor. Phys. 57, 2447–2460 (2018)

    Article  MathSciNet  Google Scholar 

  10. Wang, J., Jiang, N., Wang, L.: Quantum image translation. Quantum Inf. Process. 14, 1589–1604 (2015). https://doi.org/10.1007/s11128-014-0843-6

    Article  ADS  MathSciNet  MATH  Google Scholar 

  11. Zhou, R.G., Tan, C., Ian, H.: Global and local translation designs of quantum image based on FRQI. Int. J. Theor. Phys. 56, 1382–1398 (2017). https://doi.org/10.1007/s10773-017-3279-9

    Article  MathSciNet  MATH  Google Scholar 

  12. Yan, F., Iliyasu, A.M., Le, P.Q.: Quantum image processing: a review of advances in its security technologies. Int. J. Quantum Inf. 15, 1730001 (2017). https://doi.org/10.1142/S0219749917300017

    Article  MathSciNet  MATH  Google Scholar 

  13. Jiang, N., Wang, L., Wu, W.Y.: Quantum Hilbert image scrambling. Int. J. Theor. Phys. 53, 2463–2484 (2014). https://doi.org/10.1007/s10773-014-2046-4

    Article  MATH  Google Scholar 

  14. Jiang, N., Wu, W.Y., Wang, L.: The quantum realization of Arnold and Fibonacci image scrambling. Quantum Inf. Process. 13, 1223–1236 (2014). https://doi.org/10.1007/s11128-013-0721-7

    Article  ADS  MathSciNet  MATH  Google Scholar 

  15. Zhou, R.G., Sun, Y.J., Fan, P.: Quantum image gray-code and bit-plane scrambling. Quantum Inf. Process. 14, 1717–1734 (2015). https://doi.org/10.1007/s11128-015-0964-6

    Article  ADS  MathSciNet  MATH  Google Scholar 

  16. Zhang, W.-W., Gao, F., Liu, B., Wen, Q.-Y., Chen, H.: A watermark strategy for quantum images based on quantum Fourier transform. Quantum Inf. Process. 12, 793–803 (2013). https://doi.org/10.1007/s11128-012-0423-6

    Article  ADS  MathSciNet  MATH  Google Scholar 

  17. Song, X.H., Wang, S., Liu, S., Abd El-Latif, A.A., Niu, X.M.: A dynamic watermarking scheme for quantum images using quantum wavelet transform. Quantum Inf. Process. 12, 3689–3706 (2013). https://doi.org/10.1007/s11128-013-0629-2

    Article  ADS  MathSciNet  MATH  Google Scholar 

  18. Song, X., Wang, S.A., Abd El-Latif, A., Niu, X.: Dynamic watermarking scheme for quantum images based on Hadamard transform. Multimed. Syst. 20, 379–388 (2014). https://doi.org/10.1007/s00530-014-0355-3

    Article  Google Scholar 

  19. Jiang, N., Wang, L.: A novel strategy for quantum image steganography based on moire pattern. Int. J. Theor. Phys. 54, 1021–1032 (2015). https://doi.org/10.1007/s10773-014-2294-3

    Article  MATH  Google Scholar 

  20. Jiang, N., Zhao, N., Wang, L.: LSB based quantum image steganography algorithm. Int. J. Theor. Phys. 55, 107–123 (2015). https://doi.org/10.1007/s10773-015-2640-0

    Article  MATH  Google Scholar 

  21. Sang, J., Wang, S., Li, Q.: Least significant qubit algorithm for quantum images. Quantum Inf. Process. 15, 4441–4460 (2016). https://doi.org/10.1007/s11128-016-1411-z

    Article  ADS  MathSciNet  MATH  Google Scholar 

  22. Miyake, S., Nakamae, K.: A quantum watermarking scheme using simple and small-scale quantum circuits. Quantum Inf. Process. 15, 1849–1864 (2016). https://doi.org/10.1007/s11128-016-1260-9

    Article  ADS  MathSciNet  MATH  Google Scholar 

  23. Heidari, S., Pourarian, M.R., Gheibi, R., Naseri, M., Houshmand, M.: Quantum red–green–blue image steganography. Int. J. Quantum Inf. 15, 1750039 (2017). https://doi.org/10.1142/S0219749917500393

    Article  MathSciNet  MATH  Google Scholar 

  24. Naseri, M., Heidari, S., Baghfalaki, M., Fatahi, N., Gheibi, R., Farouk, A., Habibi, A.: A new secure quantum watermarking scheme. Optik (Stuttg) 139, 77–86 (2017). https://doi.org/10.1016/j.ijleo.2017.03.091

    Article  ADS  Google Scholar 

  25. Zhou, R.G., Hu, W., Fan, P.: Quantum watermarking scheme through Arnold scrambling and LSB steganography. Quantum Inf. Process. 16, 212–232 (2017). https://doi.org/10.1007/s11128-017-1640-9

    Article  ADS  MathSciNet  MATH  Google Scholar 

  26. Li, P., Zhao, Y., Xiao, H., Cao, M.: An improved quantum watermarking scheme using small-scale quantum circuits and color scrambling. Quantum Inf. Process. 16, 127–160 (2017). https://doi.org/10.1007/s11128-017-1577-z

    Article  ADS  MATH  Google Scholar 

  27. Zhou, R.-G., Hu, W., Fan, P., Luo, G.: Quantum color image watermarking based on Arnold transformation and LSB steganography. Int. J. Quantum Inf. 16, 1850021 (2018). https://doi.org/10.1142/S0219749918500211

    Article  MathSciNet  MATH  Google Scholar 

  28. Luo, G., Zhou, R., Hu, W., Luo, J., Liu, X., Ian, H.: Enhanced least significant qubit watermarking scheme for quantum images. Quantum Inf. Process. 17, 299 (2018). https://doi.org/10.1007/s11128-018-2075-7

    Article  ADS  MATH  Google Scholar 

  29. Wu, D.C., Tsai, W.H.: A steganographic method for images by pixel-value differencing. Pattern Recognit. Lett. 24, 1613–1626 (2003). https://doi.org/10.1016/S0167-8655(02)00402-6

    Article  MATH  Google Scholar 

  30. Chang, K.C., Chang, C.P., Huang, P.S., Tu, T.M.: A novel image steganographic method using tri-way pixel-value differencing. J. Multimed. 3, 37–44 (2008). https://doi.org/10.4304/jmm.3.2.37-44

    Article  Google Scholar 

  31. Tirkel, A.Z., Rankin, G.A., van Schyndel, R.G., Ho, W.J., Osborne, C.F.: Electronic watermark. In: Proceedings of Digital Image Computing: Techniques and Applications, pp. 666–672 (1993)

  32. Zhou, R., Hu, W., Liu, X., Fan, P., Luo, G.: Quantum realization of the nearest neighbor value interpolation method for INEQR. Quantum Inf. Process. 17, 166 (2018). https://doi.org/10.1007/s11128-018-1921-y

    Article  ADS  MathSciNet  MATH  Google Scholar 

  33. Dong, W., Kaifeng, H.: Design of quantum comparator based on extended general Toffoli gates with multiple targets. Comput. Sci. 39, 302–306 (2012)

    Google Scholar 

  34. Fridrich, J.: Reliable detection of LSB steganography in color and grayscale images. In: ACM Workshop on Multimedia and Security, pp. 27–30 (2001)

Download references

Acknowledgements

This work is supported by the National Key R&D Plan under Grant Nos. 2018YFC1200200 and 2018YFC1200205, National Natural Science Foundation of China under Grant No. 61463016, and “Science and technology innovation action plan” of Shanghai in 2017 under Grant No. 17510740300.

Author information

Authors and Affiliations

  1. College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China

    Gaofeng Luo, Ri-Gui Zhou, Jia Luo, WenWen Hu & Yang Zhou

  2. College of Information Engineering, Shaoyang University, Shaoyang, 422000, Hunan, China

    Gaofeng Luo

  3. Institute of Applied Physics and Materials Engineering, FST, University of Macau, Macau, China

    Hou Ian

Authors
  1. Gaofeng Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ri-Gui Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jia Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. WenWen Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yang Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hou Ian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ri-Gui Zhou.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Luo, G., Zhou, RG., Luo, J. et al. Adaptive LSB quantum watermarking method using tri-way pixel value differencing. Quantum Inf Process 18, 49 (2019). https://doi.org/10.1007/s11128-018-2165-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11128-018-2165-6

Keywords