Quantum multi-level wavelet transforms

Abstract The classical wavelet transform has been widely applied in the information processing field. It implies that quantum wavelet transform (QWT) may play an important role in quantum information processing. In this paper, we present the iteration equations of the general QWT using generalized tensor product. Then, Haar QWT (HQWT), Daubechies D4 QWT (DQWT), and their inverse transforms are proposed respectively. Meanwhile, the circuits of the two kinds of multi-level HQWT are designed. What’s more, the multi-level DQWT based on the periodization extension is implemented for the first time. The complexity analysis shows that the proposed multi-level QWTs on 2n elements can be implemented by O(n3) basic operations. Simulation experiments demonstrate that the proposed QWTs are correct and effective.

[1]  He Lei,et al.  Novel quantum image encryption using one-dimensional quantum cellular automata , 2016, Inf. Sci..

[2]  Kaoru Hirota,et al.  A flexible representation of quantum images for polynomial preparation, image compression, and processing operations , 2011, Quantum Inf. Process..

[3]  Shen Wang,et al.  A Novel Encryption Algorithm for Quantum Images Based on Quantum Wavelet Transform and Diffusion , 2014, ECC.

[4]  Ahmed A. Abd El-Latif,et al.  A dynamic watermarking scheme for quantum images using quantum wavelet transform , 2013, Quantum Information Processing.

[5]  Safya Belghith,et al.  Chaos-based partial image encryption scheme based on linear fractional and lifting wavelet transforms , 2017 .

[6]  Qingxin Zhu,et al.  Multidimensional color image storage, retrieval, and compression based on quantum amplitudes and phases , 2014, Inf. Sci..

[7]  Jelena Stajic,et al.  The Future of Quantum Information Processing , 2013 .

[8]  Xiangjian He,et al.  The multi-level and multi-dimensional quantum wavelet packet transforms , 2018, Scientific Reports.

[9]  Ping Fan,et al.  Quantum Implementation Circuits of Quantum Signal Representation and Type Conversion , 2019, IEEE Transactions on Circuits and Systems I: Regular Papers.

[10]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Ahmed El-Rafei,et al.  Signal and image compression using quantum discrete cosine transform , 2019, Inf. Sci..

[12]  Qingxin Zhu,et al.  Multi-dimensional color image storage and retrieval for a normal arbitrary quantum superposition state , 2014, Quantum Inf. Process..

[13]  N. Jing,et al.  Geometric transformations of multidimensional color images based on NASS , 2016, Inf. Sci..

[14]  Lov K. Grover A fast quantum mechanical algorithm for database search , 1996, STOC '96.

[15]  D L Shepelyansky,et al.  Imperfection effects for multiple applications of the quantum wavelet transform. , 2003, Physical review letters.

[16]  Ping Fan,et al.  Quantum realization of the bilinear interpolation method for NEQR , 2017, Scientific Reports.

[17]  Guowu Yang,et al.  Optimal synthesis of multiple output Boolean functions using a set of quantum gates by symbolic reachability analysis , 2006, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[18]  Haiying Xia,et al.  A Quantum Image Representation Based on Bitplanes , 2018, IEEE Access.

[19]  Lin Wu,et al.  Efficient Multi-Input/Multi-Output VLSI Architecture for Two-Dimensional Lifting-Based Discrete Wavelet Transform , 2011, IEEE Transactions on Computers.

[20]  R. Coifman,et al.  Fast wavelet transforms and numerical algorithms I , 1991 .

[21]  Patrick J. Van Fleet,et al.  Wavelet Theory: An Elementary Approach with Applications , 2009 .

[22]  Xiaoming Chang,et al.  An intelligent noise reduction method for chaotic signals based on genetic algorithms and lifting wavelet transforms , 2013, Inf. Sci..

[23]  Gunnar Karlsson,et al.  Extension of finite length signals for sub-band coding , 1989 .

[24]  Khaled Loukhaoukha,et al.  A new reliable optimized image watermarking scheme based on the integer wavelet transform and singular value decomposition for copyright protection , 2017, Inf. Sci..

[25]  D. Deutsch Quantum theory, the Church–Turing principle and the universal quantum computer , 1985, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[26]  Barenco,et al.  Elementary gates for quantum computation. , 1995, Physical review. A, Atomic, molecular, and optical physics.

[27]  Haiying Xia,et al.  Quantum vision representations and multi-dimensional quantum transforms , 2019, Inf. Sci..

[28]  V. Ralph Algazi,et al.  A Unified Treatment of Discrete Fast Unitary Transforms , 1977, SIAM J. Comput..

[29]  DiVincenzo,et al.  Five two-bit quantum gates are sufficient to implement the quantum Fredkin gate. , 1996, Physical review. A, Atomic, molecular, and optical physics.

[30]  Amir Fijany,et al.  Quantum Wavelet Transforms: Fast Algorithms and Complete Circuits , 1998, QCQC.

[31]  Tsutomu Maruyama,et al.  Max-plus algebra-based wavelet transforms and their FPGA implementation for image coding , 2010, Inf. Sci..

[32]  Kai Lu,et al.  NEQR: a novel enhanced quantum representation of digital images , 2013, Quantum Information Processing.

[33]  I. Chuang,et al.  Quantum Computation and Quantum Information: Introduction to the Tenth Anniversary Edition , 2010 .

[34]  Xiangjian He,et al.  The quantum Fourier transform based on quantum vision representation , 2018, Quantum Inf. Process..

[35]  Fei Yan,et al.  Quantum image rotation by an arbitrary angle , 2017, Quantum Inf. Process..