Abstract
In this paper, we propose a novel quantum representation of color digital images (NCQI) in quantum computer. The freshly proposed quantum image representation uses the basis state of a qubit sequence to store the RGB value of each pixel. All pixels are stored into a normalized superposition state and can be operated simultaneously. Comparison results with the latest multi-channel representation for quantum image reveal that NCQI can achieve a quadratic speedup in quantum image preparation. Meanwhile, some NCQI-based image processing operations are discussed. Analyses and comparisons demonstrate that many color operations can be executed conveniently based on NCQI. Therefore, the proposed NCQI model is more flexible and better suited to carry out color quantum image processing.
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References
Benioff, P.: The computer as a physical system: a microscopic quantum mechanical Hamiltonian models of computers as represented by Turing machines. J. Stat. Phys. 22(5), 563–591 (1980)
Feynman, R.P.: Simulating physics with computers. Int. J. Theor. Phys. 21(6/7), 467–488 (1982)
Grover, L.K.: Quantum mechanics helps in searching for a needle in a haystack. Phys. Rev. Lett. 79, 325 (1997)
Long, G.L.: Grover algorithm with zero theoretical failure rate. Phys. Rev. A 64(2), 022307 (2001)
Ai, Q., Li, Y.S., Long, G.L.: Influences of gate operation errors in the quantum counting algorithm. J. Sci. Technol. 21, 927 (2007)
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)
Venegas-Andraca, S.E., Ball, J.L., Burnett, K., Bose, S.: Processing images in entangled quantum systems. Quantum Inf. Process. 9, 1–11 (2010)
Latorre, J.I.:Image compression and entanglement. arXiv:quant-ph/0510031 (2005)
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 (2010)
Sun, B., Le, P.Q., Iliyasu, A.M.: A multi-channel representation for images on qunatum computers using the \(RGB\alpha \) color space. In: IEEE 7th International Symposium on Intelligent Signal Processing, Floriana, Malta, 2011, pp. 1–6 (2011)
Li, H.S., Zhu, Q.X., Zhou, R.G., Li, M.C., et al.: Multidimensional color image storage, retrieval, and compression based on qunatum amplitudes and phases. Inf. Sci. 273, 212–232 (2014)
Zhang, Y., Lu, K., Gao, Y.H., Xu, K.: A novel quantum representation for log-polar images. Quantum Inf. Process. 12(9), 3103–3126 (2013)
Zhang, Y., Lu, K., Gao, Y.H., Wang, M.: NEQR: a novel enhanced quantum representation of digital images. Quantum Inf. Process. 12(8), 3340–3343 (2013)
Wang, J., Jiang, N., Wang, L.: Quantum image translation. Quantum Inf. Process. 14(5), 1589–1604 (2014)
Zhang, Y., Lu, K., Xu, K., Gao, Y.H.: Local feature point extraction for quantum images. Quantum Inf. Process. 14(5), 1573–1588 (2015)
Le, P.Q., Iliyasu, A.M., Dong, F.Y., Hirota, K.: Fast geometric transformation on qunatum images. IAENG Int. J. Appl. Math. 40(3), 113–123 (2010)
Jiang, N., Wang, L.: Quantum image scaling using nearest neighbor interpolation. Quantum Inf. Process. 14(5), 1559–1571 (2014)
Sang, J.Z., Wang, S., Niu, X.M.: Quantum realization of the nearest-neighbor interpolation method for FRQI and NEQR. Quantum Inf. Process. 15, 37–64 (2016)
Acknowledgements
This work is supported by the National Science Foundation of China (61301099, 61100178, 61361166006, and 11201100). We deeply thanks the previous researcher’s work about NEQR. Thanks are due to many anonymous reviewers for their assistance with the discussion about our work.
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Sang, J., Wang, S. & Li, Q. A novel quantum representation of color digital images. Quantum Inf Process 16, 42 (2017). https://doi.org/10.1007/s11128-016-1463-0
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DOI: https://doi.org/10.1007/s11128-016-1463-0