A dual quantum image scrambling method

  • Shahrokh Heidari
  • Matin Vafaei
  • Monireh HoushmandEmail author
  • Narges Tabatabaey-Mashadi


Considering blindness in information security, image scrambling method is defined as a procedure by which an image is turned into an absolutely different meaningless image through a reversible transformation. By scrambling an image, the ability to resist against unauthorized attacks and accordingly, augmenting security can be obtained effectively. In this approach, a quantum representation of a digital scrambling algorithm is investigated for quantum NCQI color images. Experimental consequences encompassing histogram diagram, entropy rate, correlation coefficient and number of pixels change ratio, which are analyzed in MATLAB environment, indicate a good performance, showing that the proposed method is much more secure and applicable than the previous one currently found in the literature related to the quantum image disordering methods.


Quantum image processing Image scrambling NCQI color image 



The first author acknowledges the support of Kermanshah Branch, Young Researchers and Elite club, IRAN, and also would like to thank Besharat Rabiei, for her interest in this work.


  1. 1.
    Gupta, S., Goyal, A., Bhushan, B.: Information hiding using least significant bit steganography and cryptography. Int. J. Educ. Comput. Sci. 6, 27–34 (2012)CrossRefGoogle Scholar
  2. 2.
    Tsai, P., Hu, Y.U., Chang, C.C.: A color image watermarking scheme based on color quantization. Signal Process. 84(1), 95–106 (2004)zbMATHCrossRefGoogle Scholar
  3. 3.
    Yan, F., Iliyasu, A.M., Venegas-Andraca, S.E.: A survey of quantum image representations. Quantum Inf. Process. 15(1), 1–35 (2016)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Venegas-Andraca, S.E., Bose, S.: Storing, processing, and retrieving an image using quantum mechanics.In: Proceedings of SPIE Conference of Quantum Information and Computation, vol. 5105, pp. 134–147 (2003)Google Scholar
  5. 5.
    Latorre, J.: Image compression and entanglement. arXiv:quant-ph/0510031 (2005)
  6. 6.
    Le, P., Dong, F., Hitora, K.: A flexible representation of quantum images for polynomial preparation, image compression, and processing operations. Quantum Inf. Process. 10(1), 63–84 (2011)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Sun, B., Iliyasu, A., Yan, F., Dong, F., Hitora, K.: An RGB multi-channel representation for images on quantum computers. J. Adv. Comput. Intell. Intell. Inf. 17(3), 404–417 (2013)CrossRefGoogle Scholar
  8. 8.
    Zhang, Y., Lu, K., Gao, Y., Wang, M.: NEQR: a novel enhanced quantum representation of digital images. Quantum Inf. Process. 12(8), 2833–2860 (2013)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Zhang, Y., Lu, K., Gao, Y., Xu, K.: A novel quantum representation for log-polar images. Quantum Inf. Process. 12(9), 3103–3126 (2013)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  10. 10.
    Yuan, S., Mao, X., Xue, Y., Chen, L., Xiong, Q., Compare, A.: SQR: a simple quantum representation of infrared images. Quantum Inf. Process. 13(6), 1353–1379 (2014)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Abdolmaleky, M., et al.: Red–green–blue multi-channel quantum representation of digital images. Optik 128, 121–132 (2017)ADSCrossRefGoogle Scholar
  12. 12.
    Sang, J.Z., Wang, S., Li, Q.: A novel quantum representation for color digital images. Quantum Inf. Process. 16(2), 42 (2017)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    Jiang, N., Dang, Y., Wang, J.: Qauntum image matching. Quantum Inf. Process. 15(0, 3543–3572 (2016)ADSzbMATHCrossRefGoogle Scholar
  14. 14.
    Jiang, N., Dang, Y., Zhao, N.: Quantum image location. Int. J. Theor. Phys. 55(10), 4501–4512 (2016)zbMATHCrossRefGoogle Scholar
  15. 15.
    Yuan, S., Mao, X., Zhou, J., Wang, X.: Quantum image filtering in the spatial domain. Int. J. Theor. Phys. 56, 1–17 (2017)zbMATHCrossRefGoogle Scholar
  16. 16.
    Iliyasu, A., Le, P., Dong, F., Hitora, K.: Watermarking and authentication of quantum images based on restricted geometric transformations. Inf. Sci. 186(1), 126–149 (2012)MathSciNetzbMATHCrossRefGoogle Scholar
  17. 17.
    Zhang, W., Gao, F., Liu, B., Jia, H.: A quantum watermark protocol. Int. J. Theor. Phys. 52(2), 504–513 (2013)MathSciNetzbMATHCrossRefGoogle Scholar
  18. 18.
    Song, X., Wang, S., Liu, S., Abd El-Latif, A., Niu, X.: A dynamic watermarking scheme for quantum images using quantum wavelet transform. Quantum Inf. Process. 12(2), 3689–3706 (2013)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  19. 19.
    Song, X., Wang, S., Abd El-Latif, A., Niu, X.: Dynamic watermarking scheme for quantum images based on hadamard transform. Multimed. Syst. 20(4), 379–388 (2014)CrossRefGoogle Scholar
  20. 20.
    Jiang, N., Wang, L.: A novel strategy for quantum image steganography based on Moiré pattern. Int. J. Theor. Phys. 54(3), 1021–1032 (2015)zbMATHCrossRefGoogle Scholar
  21. 21.
    Wang, S., et al.: Least significant qubit (LSQb) information hiding algorithm for quantum image. Measurement 73, 352–359 (2015)CrossRefGoogle Scholar
  22. 22.
    Jiang, N., Zhao, N., Wang, L.: LSB based quantum image steganography algorithm. Int. J. Theor. Phys. 55, 107–123 (2016)zbMATHCrossRefGoogle Scholar
  23. 23.
    Miyake, S., Nakamae, K.: A quantum watermarking scheme using simple and smallscale quantum circuits. Quantum Inf. Process. 15, 1849–1864 (2016)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  24. 24.
    Sang, J., Wang, S., Li, Q.: Least significant qubit algorithm for quantum images. Quantum Inf. Process. 15(11), 4441–4460 (2016)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  25. 25.
    Heidari, S., Naseri, M.: A novel LSB based quantum image watermarking. Int. J. Theor. Phys. 55(10), 4205–4218 (2016)zbMATHCrossRefGoogle Scholar
  26. 26.
    Naseri, M., Heidari, S., et al.: A new secure quantum watermarking scheme. Optik 139, 77–86 (2017)ADSCrossRefGoogle Scholar
  27. 27.
    Heidari, S., Gheibi, R., Houshmand, M., Nagata, K.: A robust blind quantum copyright protection method for colored images based om owner’s signature. Int. J. Theor. Phys. 56(8), 2562–2578 (2017)zbMATHCrossRefGoogle Scholar
  28. 28.
    Heidari, S., et al.: A new quantum watermarking based on quantum wavelet transforms. Commun. Theor. Phys. 67(6), 732–742 (2017)ADSMathSciNetCrossRefGoogle Scholar
  29. 29.
    Naseri, M., Heidari, S., Gheibi, R., Gong, L.H., Raji, M.A., Sadri, A.: A novel quantum binary images thining algorithm: a quantum version of the Hilditch’s algorithm. Optik 131, 678–686 (2017)ADSCrossRefGoogle Scholar
  30. 30.
    Heidari, S., Farzadnia, E.: A novel quantum LSB-based steganography method using the gray code for colored quantum images. Quantum Inf. Process. 16(10), 242 (2017)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  31. 31.
    Heidari, S., Pourarian, M.R., Gheibi, R., Naseri, M., Houshmand, M.: Quantum red-green-blue image steganography. Int. J. Quantum Infor. 15(05), 1750039 (2017)MathSciNetzbMATHCrossRefGoogle Scholar
  32. 32.
    Jiang, N., Wu, W.Y., Wang, L.: The quantum realization of Arnold and Fibonacci image scrambling. Quantum Inf. Process. 13(5), 1223–1236 (2014)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  33. 33.
    Jiang, N., Wang, L., Wu, W.Y.: Quantum Hilbert image scrambling. Int. J. Theor. Phys. 53(7), 2463–2484 (2014)zbMATHCrossRefGoogle Scholar
  34. 34.
    Jiang, N., Wang, L.: Analysis and improvement of the quantum Arnold image scrambling. Quantum Inf. Process. 13(7), 1545–1551 (2014)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  35. 35.
    Zhou, R.G., Sun, Y.J., Fan, P.: Quantum image gray-code and bit-plane scrambling. Quantum Inf. Process. 14(5), 1717–2734 (2015)ADSMathSciNetzbMATHCrossRefGoogle Scholar
  36. 36.
    Anushiadevi, R., et al.: Revolving of pixels and bits in pixels-plan (E) Tray encryption. Res. J. Inf. Thechnol. 9, 25–31 (2017)Google Scholar
  37. 37.
    Shende. V.V., Markov, I.L.: On the CNOT-cost of Toffoli gates. arXiv preprint arXiv:0803.2316 (2008)
  38. 38.
    Jagadeesh, P., Nagabhushan, P., Pradeep Kumar, R.: A novel image scrambling technique based on information entropy and quad tree decomposition. Int. J. Comput. Sci. Issues 10(2), 1694–784 (2013)Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Shahrokh Heidari
    • 1
  • Matin Vafaei
    • 2
  • Monireh Houshmand
    • 2
    Email author
  • Narges Tabatabaey-Mashadi
    • 2
  1. 1.Young Researchers and Elite Club, Kermanshah BranchIslamic Azad UniversityKermanshahIran
  2. 2.Department of Electrical EngineeringImam Reza International UniversityMashhadIran

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