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Quantum image with high retrieval performance

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Abstract

Quantum image retrieval is an exhaustive work due to exponential measurements. Casting aside the background of image processing, quantum image is a pure many-body state, and the retrieval task is a physical process named as quantum state tomography. Tomography of a special class of states, permutationally symmetric states, just needs quadratic measurement scales with the number of qubits. In order to take advantage of this result, we propose a method to map the main energy of the image to these states. First, we deduce that \(n+1\) permutationally symmetric states can be constructed as bases of \(2^n\) Hilbert space (n qubits) at least. Second, we execute Schmidt decomposition by continually bipartite splitting of the quantum image (state). At last, we select \(n+1\) maximum coefficients, do base transformation to map these coefficients to new bases (permutationally symmetric states). By these means, the quantum image with high retrieval performance can be gotten.

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References

  1. Feynman, R.P.: Simulating physics with computers. Int. J. Theor. Phys. 21, 467–488 (1982)

    Article  MathSciNet  Google Scholar 

  2. Vlaso, A.Y.: Quantum Computations and Images Recognition. arXiv:quant-ph/9703010 (1997)

  3. Venegas-Andraca, S.E., Bose, S.: Storing, processing and retrieving an image using quantum mechanics. Proc. SPIE Conf. Quantum Inf. Comput. 5105, 137–147 (2003)

    ADS  Google Scholar 

  4. Venegas-Andraca, S.E.: Discrete Quantum Walks and Quantum Image Processing. Thesis submitted for the degree of Doctor of Philosophy at the University of Oxford (2005). http://mindsofmexico.org/sva/dphil

  5. Latorre, J.I.: Image Compression and Entanglement. arXiv:quant-ph/0510031 (2005)

  6. 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)

    Article  MathSciNet  MATH  Google Scholar 

  7. 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)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  8. Wang, M., Lu, K., Zhang, Y.: FLPI: representation of quantum images for log-polar coordinate. In: Proceedings of the Fifth International Conference on Digital Image Processing (ICDIP 2013), Beijing, China, pp. 1–5 (2013)

  9. Zhang, Y., Lu, K., Gao, Y., Wang, M.: A novel quantum representation for log-polar images. Quantum Inf. Process. 12(8), 3103–3126 (2013)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  10. 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  MATH  Google Scholar 

  11. 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  MATH  Google Scholar 

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

    Article  ADS  MathSciNet  MATH  Google Scholar 

  13. Quantum Tomography. http://en.wikipedia.org/wiki/Quantum_tomography

  14. Gross, D., Liu, Y.K., Flammia, S., Becker, S., Eisert, J.: Quantum state tomography via compressed sensing. Phy. Rev. Lett. 105, 150401 (2010)

    Article  ADS  Google Scholar 

  15. Permutationally Invariant Quantum Tomography. http://www.pitomography.eu

  16. Tóth, G., Wieczorek, W., Gross, D., et al.: Permutationally invariant quantum tomography. Phy. Rev. Lett. 105, 250403 (2010)

    Article  ADS  Google Scholar 

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

    MATH  Google Scholar 

  18. Vidal, G.: Efficient classical simulation of slightly entangled quantum computations. Phy. Rev. Lett. 91, 147902 (2003)

    Article  ADS  Google Scholar 

  19. Vidal, G.: Efficient simulation of one-dimensional quantum many-body systems. Phy. Rev. Lett. 93, 040502 (2004)

    Article  ADS  Google Scholar 

Download references

Acknowledgments

This work is supported by the National Natural Science Foundation of China (Grant No. 61170321,61502101), Natural Science Foundation of Jiangsu Province, China (Grant No. BK20140651), Research Fund for the Doctoral Program of Higher Education (Grant No. 20110092110024) and the open fund of Key Laboratory of Computer Network and Information Integration In Southeast University, Ministry of Education, China (Grant No. K93-9-2015-10C).

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Correspondence to Hanwu Chen.

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Ruan, Y., Chen, H., Liu, Z. et al. Quantum image with high retrieval performance. Quantum Inf Process 15, 637–650 (2016). https://doi.org/10.1007/s11128-015-1208-5

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  • DOI: https://doi.org/10.1007/s11128-015-1208-5

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