Skip to main content
Log in

A comment on “Quantum image processing?”

  • Comment
  • Published:
Quantum Information Processing Aims and scope Submit manuscript

A Reply to Comment to this article was published on 30 March 2020

The Original Article was published on 20 December 2016

Abstract

This comment analyzes and clarifies some questions proposed by Mastriani (Quantum Inf Process 16:27, 2017). These questions include the distinction between simulation verifications and quantum algorithms, the classical-to-quantum and quantum-to-classical interfaces, quantum measurement problem. Firstly, we propose that these questions are confusion, and even wrong. Then, we analyze the storage and computing performances of quantum Boolean image processing (QuBoIP), and conclude that QuBoIP has almost no significance for development of quantum image processing. Meanwhile, we describe how to verify the correctness of quantum algorithms using Matlab, and consider that the simulation verification of quantum algorithms is feasible on classic computers. Although quantum measurement is the open issue of quantum image processing, quantum image processing deserves further research and are significant. In conclusion, we believe that this comment is helpful for the developing of quantum image processing by clarifying these confusing questions proposed by Mario Mastriani.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Shor, P.W.: Algorithms for quantum computation: discrete logarithms and factoring. In: Proceedings of 35th Annual Symposium on Foundations of Computer Science, pp. 124–134. IEEE (1994)

  2. Deutsch, D.: Quantum theory, the Church-Turing principle and the universal quantum computer. Proc. R. Soc. Lond. A Math. Phys. Eng. Sci. 400, 97–117 (1985)

    ADS  MathSciNet  MATH  Google Scholar 

  3. Nielsen, M.A., Chuang, I.L.: Quantum Computation and Quantum Information. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  4. Beach, G., Lomont, C., Cohen, C.: Quantum image processing (QuIP). In: Proceedings of IEEE 32nd Applied Imagery Pattern Recognition Workshop, pp. 39–44 (2003)

  5. Venegas-Andraca, S.E., Bose, S.: Quantum computation and image processing: new trends in artificial intelligence. In: Proceedings of the International Congress on Artificial Intelligence, pp. 1563–1564 (2003)

  6. Venegas-Andraca, S.E., Bose, S.: Storing, processing, and retrieving an image using quantum mechanics. In: Proceedings of the SPIE Conference on Quantum Information and Computation, pp. 137–147 (2003)

  7. 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)

    Article  MathSciNet  Google Scholar 

  8. Sun, B., Iliyasu, A., Yan, F., et al.: An rgb multi-channel representationfor images on quantum computers. J. Adv. Comput. Intell. Intell. Inform. 17(3), 404–417 (2013)

    Article  Google Scholar 

  9. Li, H.S., Zhu, Q., Song, L., et al.: Image storage, retrieval, compression and segmentation in a quantum system. Quantum Inf. Process. 12(6), 2269–2290 (2013)

    Article  ADS  MathSciNet  Google Scholar 

  10. Li, H.S., Zhu, Q., Zhou, R.G., et al.: Multidimensional color image storage, retrieval, and compression based on quantum amplitudes and phases. Inf. Sci. 273, 212–232 (2014)

    Article  Google Scholar 

  11. Li, H.S., Zhu, Q., Zhou, R.G., et al.: Multi-dimensional color image storage and retrieval for a normal arbitrary quantum superposition state. Quantum Inf. Process. 13(4), 991–1011 (2014)

    Article  ADS  MathSciNet  Google Scholar 

  12. Li, H.S., Fan, P., Xia, H.Y., et al.: Quantum implementation circuits of quantum signal representation and type conversion. IEEE Trans. Circuits Syst. I Regul. Pap. 99, 1–14 (2018)

    Article  Google Scholar 

  13. Zhou, R.G., Wu, Q., Zhang, M.Q., et al.: Quantum image encryption and decryption algorithms based on quantum image geometric transformations. Int. J. Theor. Phys. 52(6), 1802–1817 (2013)

    Article  MathSciNet  Google Scholar 

  14. Zhang, Y., Lu, K., Gao, Y., et al.: NEQR: a novel enhanced quantum representation of digital images. Quantum Inf. Process. 12(8), 2283–2860 (2013)

    ADS  MathSciNet  MATH  Google Scholar 

  15. Yuan, S., Mao, X., Xue, Y., et al.: SQR: a simple quantum representation of infrared images. Quantum Inf. Process. 13(6), 1353–1379 (2014)

    Article  ADS  MathSciNet  Google Scholar 

  16. Yan, F.F., Iliyasu, A.M., Venegas-Andraca, S.E.: survey of quantum image representations. Quantum Inf. Process. 15, 1–35 (2016)

    Article  ADS  MathSciNet  Google Scholar 

  17. Yan, F.F., Iliyasu, A.M., Jiang, Z.: Quantum computation-based image representation, processing operations and their applications. Entropy 16, 5290–5338 (2014)

    Article  ADS  MathSciNet  Google Scholar 

  18. Jiang, N., Wang, L.: Quantum image scaling using nearest neighbor interpolation. Quantum Inf. Process. 14(5), 1559–1571 (2015)

    Article  ADS  MathSciNet  Google Scholar 

  19. Abdolmaleky, M., Naseri, M., Batle, J., et al.: Red–Green–Blue multi-channel quantum representation of digital images. Optik 128, 121–132 (2017)

    Article  ADS  Google Scholar 

  20. Yang, Y.G., Xia, J., Jia, X., et al.: Novel image encryption/decryption based on quantum Fourier transform and double phase encoding. Quantum Inf. Process. 12(11), 3477–3493 (2013)

    Article  ADS  MathSciNet  Google Scholar 

  21. Sang, J., Wang, S., Li, Q.: A novel quantum representation of color digital images. Quantum Inf. Process. 16(2), 1–14 (2017)

    Article  ADS  MathSciNet  Google Scholar 

  22. Li, H.S., Chen, X., Xia, H., et al.: A quantum image representation based on bitplanes. IEEE Access 6, 62396–62404 (2018)

    Article  Google Scholar 

  23. Li, H.S., Fan, P., Xia, H.Y., et al.: The quantum Fourier transform based on quantum vision representation. Quantum Inf. Process. 17(12), 333 (2018)

    Article  ADS  MathSciNet  Google Scholar 

  24. Li, H.S., Fan, P., Xia, H.Y., et al.: The multi-level and multi-dimensional quantum wavelet packet transforms. Sci. Rep. 8(1), 13884 (2018)

    Article  ADS  Google Scholar 

  25. Zhou, R.G., Hu, W., Fan, P., et al.: Quantum realization of the bilinear interpolation method for NEQR. Sci. Rep. 7(1), 2511 (2017)

    Article  ADS  Google Scholar 

  26. Pang, C.Y., Zhou, R.G., Hu, B.Q., et al.: Signal and image compression using quantum discrete cosine transform. Inf. Sci. 473, 121–141 (2019)

    Article  MathSciNet  Google Scholar 

  27. Zhou, R.G., Yang, P.L., Liu, X.A., et al.: Quantum color image watermarking based on fast bit-plane scramble and dual embedded. Int. J. Quantum Inf. 16(07), 1850060 (2018)

    Article  Google Scholar 

  28. Mastriani, M.: Quantum image processing? Quantum Inf. Process. 16, 27 (2017)

    Article  ADS  Google Scholar 

  29. Mastriani, M.: Quantum Boolean image denoising. Quantum Inf. Process. 14, 1647–1673 (2014)

    Article  ADS  MathSciNet  Google Scholar 

  30. Hung, W.N., Song, X., Yang, G., et al.: Optimal synthesis of multiple output Boolean functions using a set of quantum gates by symbolic reachability analysis. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 25, 1652–1663 (2006)

    Article  Google Scholar 

  31. Grover, L.: A fast quantum mechanical algorithm for database search. In: Proceedings of the 28th Annual ACM Symposium on the Theory of Computing, pp. 212–219 (1996)

  32. Hu, B., Huang, X., Zhou, R., et al.: A theoretical framework for quantum image representation and data loading scheme. Sci. China Inf. Sci. 57, 032108 (2014)

    MATH  Google Scholar 

  33. Lin, C.C., Chakrabarti, A., Jha, N.K.: FTQLS: fault-tolerant quantum logic synthesis. IEEE Trans. Very Large Scale Integr. Syst. 22(6), 1350–1363 (2014)

    Article  Google Scholar 

  34. Fan, P., Zhou, R.G., Jing, N., Li, H.S.: Geometric transformations of multidimensional color images based on NASS. Inf. Sci. 340, 191–208 (2016)

    Article  Google Scholar 

  35. DiVincenzo, D.P.: Two-bit gates are universal for quantum computation. Phys. Rev. A 51, 1015–1022 (1995)

    Article  ADS  Google Scholar 

  36. Yao, X., Wang, H., Liao, Z., et al.: Quantum image processing and its application to edge detection: theory and experiment. Phys. Rev. X 7, 031041 (2017)

    Google Scholar 

  37. Jiang, N., Dang, Y., Wang, J.: Quantum image matching. Quantum Inf. Process. 15, 3542–3572 (2016)

    ADS  MathSciNet  Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China under Grant Nos. 61462026, 61762012, and 61763014, the Science and Technology Project of Guangxi under Grant No. 2018JJA170083, the National Key R&D Plan under Grant Nos. 2018YFC1200200 and 2018YFC1200205, the Fund for Distinguished Young Scholars of Jiangxi Province under Grant No. 2018ACB2101, Natural Science Foundation of Jiangxi Province of China under Grant No. 20192BAB207014, Science and technology research project of Jiangxi Provincial Education Department under Grant No. GJJ190297. We thank the anonymous reviewers for their helpful feedback.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hai-Sheng Li.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This comment refers to the article available online at https://doi.org/10.1007/s11128-016-1457-y.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, HS., Fan, P., Xia, Hy. et al. A comment on “Quantum image processing?”. Quantum Inf Process 19, 155 (2020). https://doi.org/10.1007/s11128-020-02654-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11128-020-02654-0

Keywords

Navigation