Quantum Information Processing

, Volume 14, Issue 5, pp 1589–1604 | Cite as

Quantum image translation

Article

Abstract

Image translation, which maps the position of each picture element into a new position, is a basic image transformation. Although it has been deeply researched and widely used in classical image processing, its quantum version is a vacancy. This paper studies the quantum image translation (QIT) for the first time to promote the development of quantum image processing. Two types of QIT: entire translation and cyclic translation are proposed by giving the quantum translation circuits. The translation in \(X\)-direction and \(Y\)-direction is separable, and the circuits for translating right or left are different.

Keywords

Quantum image processing Image translation Quantum computation Quantum circuit 

References

  1. 1.
    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)Google Scholar
  2. 2.
    Latorre, J.I.: Image compression and entanglement (2005). arXiv:quantph/0510031
  3. 3.
    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(1), 63–84 (2011)CrossRefMATHMathSciNetGoogle Scholar
  4. 4.
    Zhang, Y., Lu, K., Gao, Y.H., et al.: NEQR: a novel enhanced quantum representation of digital images. Quantum. Inf. Process. 12(12), 2833–2833 (2013)Google Scholar
  5. 5.
    Le, P.Q., Iliyasu, A.M., Dong, F.Y., Hirota, K.: Fast geometric transformation on quantum images. IAENG Int. J. Appl. Math. 40(3), 113–123 (2010)MATHMathSciNetGoogle Scholar
  6. 6.
    Jiang, N., Wang, L.: Quantum image scaling using nearest neighbor interpolation. Quantum Inf. Process. (2014). doi: 10.1007/s11128-014-0841-8
  7. 7.
    Jiang, N., Wu, W.Y., Wang, L.: The quantum realization of Arnold and Fibonacci image scrambling. Quantum Inf. Process. 13(5), 1223–1236 (2014)CrossRefADSMATHMathSciNetGoogle Scholar
  8. 8.
    Jiang, N., Wang, L., Wu, W.Y.: Quantum Hilbert image scrambling. Int. J. Theor. Phys. 53(7), 2463–2484 (2014)CrossRefMATHGoogle Scholar
  9. 9.
    Jiang, N., Wang, L.: Analysis and improvement of the quantum Arnold image scrambling. Quantum Inf. Process. 13(7), 1545–1551 (2014)CrossRefADSMATHMathSciNetGoogle Scholar
  10. 10.
    Nielson, M.A., Chuang, I.L.: Quantum Computation and Quantum Information. Cambridge University Press, Cambridge (2000)Google Scholar
  11. 11.
    Fijany, A., Williams, C.: Quantum wavelet transform: fast algorithm and complete circuits (1998). arXiv:quantph/9809004
  12. 12.
    Klappenecker, A., Roetteler, M.: Discrete cosine transforms on quantum computers. In: IEEER8-EURASIP Symposium on Image and Signal Processing and Analysis (ISPA01), Pula, Croatia, pp. 464–468 (2001)Google Scholar
  13. 13.
    Tseng, C., Hwang, T.: Quantum circuit design of \(8\times 8\) discrete cosine transforms using its fast computation flow graph. In: IEEE International Symposium on Circuits and Systems, pp. 828–831 (2005)Google Scholar
  14. 14.
    Vlatko, V., Adriano, B., Artur, E.: Quantum networks for elementary arithmetic operations. Phys. Rev. A 54(1), 147–153 (1996)CrossRefADSMathSciNetGoogle Scholar
  15. 15.
    Wang, D., Liu, Z., Zhu, W., Li, S.: Design of quantum comparator based on extended general Toffoli gates with multiple targets. Comput. Sci. 39(9), 302–306 (2012)Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.School of Computer and Information TechnologyBeijing Jiaotong UniversityBeijingChina
  2. 2.College of ComputerBeijing University of TechnologyBeijingChina

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