Abstract
The research of quantum image processing has gradually come into the attention of scholars in recent decade. However, the existing research results on quantum image processing almost are based on binary quantum system. In a novel enhanced quantum representation of digital images model (NEQR), for a quantum image with gray scale ranging from 0 to 255, eight qubits are needed to store the information of gray value. The follow question arises. How to use fewer quantum units to store a certain amount of information? Therefore, inspired by NEQR, this paper considers some research on quantum images in ternary quantum systems. In this case, for a quantum image with gray scale ranging from 0 to 255, six qutrits are needed to store the information of gray value. Therefore, a novel qutrit representation of quantum image (QTRQ) is proposed in this paper. In order to simplify quantum circuits, the paper designs a quantum image circuit compression scheme for QTRQ, which uses ternary logic function to compress quantum circuit. What’s more, optimization rules of elimination, merger and movement are used to further simplify the circuit. An example given in this paper shows that the scheme has a fantastic result to simplify quantum circuits.




























Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.Data availability
All data and models generated or used during the study appear in the submitted article.
References
Ashikhmin, A., Knill, E.: Nonbinary quantum stabilizer codes. IEEE Trans. Inf. Theory 47(7), 3065–3072 (2000)
Beach, G., Lomont, C., Cohen, C.: Quantum image processing (QuIP). Presented at the (2004)
Charles, H.B., Shor, P.W.: Quantum information theory. IEEE Trans. Inf. Theory 44(6), 2724–2742 (2008)
Chen, G.L., Song, X., Venegas-Andraca, S., e.a.: QIRHSI: novel quantum image representation based on HSI color space model. Quantum Inf. Process. 21(5) (2022)
Feynman, R.P.: Quantum mechanical computers. Optics News 16(6), 507–531 (1986)
Gisin, N., Ribordy, G., Tittel, W., Zbinden, H.: Quantum cryptography. Rev. Modern Phys. 74(1), 145–195 (2001)
Grigoryan, A.M., Agaian, S.S.: New look on quantum representation of images: Fourier transform representation. Quantum Inf. Process 19(148) (2020)
Grover, L.K.: A fast quantum mechanical algorithm for database search. arXiv:quant-ph/9605043 (1996)
Jiang, N., Dang, Y., Wang, J.: Quantum image matching. Quantum Inf. Process. 15(9), 3543–3572 (2016)
Jiang, N., Ji, Z., Li, H.,Wang, J.: Quantum image interest point extraction. Modern Phys. Lett. A. 36(09), 2150063 (2021)
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 (2011)
Li, H., Fan, P., Xia, H., Peng, H., Long, G.: Efficient quantum arithmetic operation circuits for quantum image processing. Sci. China Phys. Mech. Astron. 63(8), 1–13 (2020)
Liu, Z., Chen, H., Xu, J., Liu, W., Li, Z.: High-dimensional deterministic multiparty quantum secret sharing without unitary operations. Quantum Inf. Process. 11(6), 1785–1795 (2012)
Muthukrishnan, A., Stroud, C.R., Jr.: Multi-valued logic gates for quantum computation. Phys. Rev. A. 65(2), 1–8 (2018)
Richards, R.K.: Arithmetic Operations in Digital Computer. Van Nostrand (1956)
Sang, J., Wang, S., Li, Q.: A novel quantum representation of color digital images. Quantum Inf. Process. 16(42), (2017)
Shor, P.W.: Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM Rev. 41(2), 303–332 (1999)
Song, X., Wang, S., Niu, X.: Multi-channel quantum image representation based on phase transform and elementary transformations. J. Inf. Hiding Multim. Signal Process. 5, 574–585 (2014)
Venegas-Andraca, S.E., Ball, J.L.: Processing images in entangled quantum systems. Quantum Inf. Process. 9(1), 1–11 (2010)
Venegas-Andraca, S.E., Bose, S.: Storing, processing, and retrieving an image using quantum mechanics. Proc. SPIE Int. Soc. Opt. Eng. 5105(10), 137–147 (2003)
Wang, B., Hao, M., Li, P., Liu, Z.: Quantum representation of indexed images and its applications. Int. J. Theor. Phys. 59(3), 374–402 (2020)
Yuan, S., Wen, C., Hang, B., Gong, Y.: The dual-threshold quantum image segmentation algorithm and its simulation. Quantum Inf. Process. 19(425), (2020)
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)
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Dong, H., Lu, D. & Li, C. A novel qutrit representation of quantum image. Quantum Inf Process 21, 108 (2022). https://doi.org/10.1007/s11128-022-03450-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11128-022-03450-8
Keywords
Profiles
- Chan Li View author profile