The linear cyclic translation and two-point swapping transformations for quantum images

Geometric transformations are fundamental operations in quantum image processing. We present quantum algorithms to realize two geometric transformations (i.e., the linear cyclic translation and two-point swapping transformations) on quantum images with $$2^n$$ pixels. The circuits for two geometric transformations are designed with the complexity O(n). Comparative analysis and simulation results reveal that the proposed cyclic translation and two-point swapping transformations are efficient.

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

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

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

[4]  Nan Jiang,et al.  A Survey on Quantum Image Processing , 2018, Chinese Journal of Electronics.

[5]  Barenco,et al.  Quantum networks for elementary arithmetic operations. , 1995, Physical review. A, Atomic, molecular, and optical physics.

[6]  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.

[7]  Dongdai Lin,et al.  Survey on cyberspace security , 2015, Science China Information Sciences.

[8]  YaoChong Li,et al.  A quantum deep convolutional neural network for image recognition , 2020, Quantum Science and Technology.

[9]  H. Ian,et al.  Global and Local Translation Designs of Quantum Image Based on FRQI , 2017, International Journal of Theoretical Physics.

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

[11]  Abdullah M. Iliyasu,et al.  Fast Geometric Transformations on Quantum Images , 2010 .

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

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

[14]  Nan Jiang,et al.  Quantum image translation , 2015, Quantum Inf. Process..

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

[16]  Zhengang Jiang,et al.  Chromatic framework for quantum movies and applications in creating montages , 2018, Frontiers of Computer Science.

[17]  Liu Yang,et al.  Search an unsorted database with quantum mechanics , 2007 .

[18]  Jun Li,et al.  Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment , 2017, 1801.01465.

[19]  Abdullah M. Iliyasu,et al.  Strategies for designing geometric transformations on quantum images , 2011, Theor. Comput. Sci..

[20]  Nan Jiang,et al.  Quantum Image Histogram Statistics , 2020 .

[21]  Huamin Yang,et al.  Flexible representation and manipulation of audio signals on quantum computers , 2017, Theor. Comput. Sci..

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

[23]  G. Long,et al.  Multilevel 2-D Quantum Wavelet Transforms , 2021, IEEE Transactions on Cybernetics.

[24]  Haiying Xia,et al.  Efficient quantum arithmetic operation circuits for quantum image processing , 2020, Science China Physics, Mechanics & Astronomy.

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

[26]  Haiying Xia,et al.  Quantum multi-level wavelet transforms , 2019, Inf. Sci..

[27]  Kaoru Hirota,et al.  Watermarking and authentication of quantum images based on restricted geometric transformations , 2012, Inf. Sci..

[28]  Kai Lu,et al.  QSobel: A novel quantum image edge extraction algorithm , 2014, Science China Information Sciences.

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

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

[31]  She-Xiang Jiang,et al.  A Quantum Mechanics-Based Framework for EEG Signal Feature Extraction and Classification , 2022, IEEE Transactions on Emerging Topics in Computing.

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

[33]  Chris Lomont,et al.  Quantum image processing (QuIP) , 2003, 32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings..

[34]  Jacob biamonte,et al.  Quantum machine learning , 2016, Nature.

[35]  Barenco,et al.  Approximate quantum Fourier transform and decoherence. , 1996, Physical review. A, Atomic, molecular, and optical physics.

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

[37]  Sougato Bose,et al.  Storing, processing, and retrieving an image using quantum mechanics , 2003, SPIE Defense + Commercial Sensing.

[38]  Peter W. Shor,et al.  Algorithms for quantum computation: discrete logarithms and factoring , 1994, Proceedings 35th Annual Symposium on Foundations of Computer Science.