Least significant qubit algorithm for quantum images
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To study the feasibility of the classical image least significant bit (LSB) information hiding algorithm on quantum computer, a least significant qubit (LSQb) information hiding algorithm of quantum image is proposed. In this paper, we focus on a novel quantum representation for color digital images (NCQI). Firstly, by designing the three qubits comparator and unitary operators, the reasonability and feasibility of LSQb based on NCQI are presented. Then, the concrete LSQb information hiding algorithm is proposed, which can realize the aim of embedding the secret qubits into the least significant qubits of RGB channels of quantum cover image. Quantum circuit of the LSQb information hiding algorithm is also illustrated. Furthermore, the secrets extracting algorithm and circuit are illustrated through utilizing control-swap gates. The two merits of our algorithm are: (1) it is absolutely blind and (2) when extracting secret binary qubits, it does not need any quantum measurement operation or any other help from classical computer. Finally, simulation and comparative analysis show the performance of our algorithm.
KeywordsLeast significant qubit Unitary operator Color digital images
This work is supported by the National Science Foundation of China (Grant Numbers: 61471141, 61301099, 61361166006), and Basic Research Project of Shenzhen, China (Grant Numbers: JCYJ20150513151706561). We deeply thanks the previous researchers’ work about NEQR. Thanks are due to many anonymous reviewers for their assistance with the discussion about the designed three qubits comparator and the quantum measurement.
- 3.Mastriani, M.: Quantum image processing? arXiv: 1512.02942 [quan-ph] (2016)
- 6.Latorre, J.I.: Image compression and entanglement. arXiv: quant-ph/0510031 (2005)
- 11.Sun, B., Le, P.Q., Iliyasu, A.M.: A multi-channel representation for images on quantum computers using the \(RGB\alpha \) color space. In: Intelligent Signal Processing, 2011 IEEE 7th International Symposium on. Floriana, Malta: IEEE. pp. 1–6 (2011)Google Scholar
- 12.Sang, J.Z., Wang, S., Li, Q.: A novel quantum representation for color digital images. Quantum Inf. Process, submitted (2016)Google Scholar
- 13.Nielson, M.A., Chuang, I.L.: Quantum Computation and Quantum Information. Cambridge University Press, Cambridge (2000)Google Scholar
- 14.Fijany, A., Williams, C.: Quantum wavelet transform: fast algorithm and complete circuits. arXiv:quant-ph/9809004 (1998)
- 15.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
- 29.Miyake, S., Nakamae, K.: A quantum watermarking scheme using simple and small-scale quantum circuits. Quantum Inf. Process. (2016). doi: 10.1007/s11128-016-1260-9
- 33.Nielsom, M.A., Chuang, I.L.: Quantum Computation and Quantum Information. Cambridfe University Press, Cambridge (2000)Google Scholar