Quantum realization of the bilinear interpolation method for NEQR

In recent years, quantum image processing is one of the most active fields in quantum computation and quantum information. Image scaling as a kind of image geometric transformation has been widely studied and applied in the classical image processing, however, the quantum version of which does not exist. This paper is concerned with the feasibility of the classical bilinear interpolation based on novel enhanced quantum image representation (NEQR). Firstly, the feasibility of the bilinear interpolation for NEQR is proven. Then the concrete quantum circuits of the bilinear interpolation including scaling up and scaling down for NEQR are given by using the multiply Control-Not operation, special adding one operation, the reverse parallel adder, parallel subtractor, multiplier and division operations. Finally, the complexity analysis of the quantum network circuit based on the basic quantum gates is deduced. Simulation result shows that the scaled-up image using bilinear interpolation is clearer and less distorted than nearest interpolation.

[1]  Nan Jiang,et al.  Analysis and improvement of the quantum Arnold image scrambling , 2014, Quantum Information Processing.

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

[3]  Shahrokh Heidari,et al.  A Novel LSB Based Quantum Watermarking , 2016, International Journal of Theoretical Physics.

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

[5]  Himanshu Thapliyal,et al.  A new design of the reversible subtractor circuit , 2011, 2011 11th IEEE International Conference on Nanotechnology.

[6]  José Ignacio Latorre,et al.  Image compression and entanglement , 2005, ArXiv.

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

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

[9]  R. Feynman Simulating physics with computers , 1999 .

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

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

[12]  Thierry Paul,et al.  Quantum computation and quantum information , 2007, Mathematical Structures in Computer Science.

[13]  N. Ranganathan,et al.  Circuit for Reversible Quantum Multiplier Based on Binary Tree Optimizing Ancilla and Garbage Bits , 2014, 2014 27th International Conference on VLSI Design and 2014 13th International Conference on Embedded Systems.

[14]  Tommaso Toffoli,et al.  Reversible Computing , 1980, ICALP.

[15]  D. M. Miller,et al.  Comparison of the Cost Metrics for Reversible and Quantum Logic Synthesis , 2005, quant-ph/0511008.

[16]  Muhammad Mahbubur Rahman,et al.  Low Cost Quantum Realization of Reversible Multiplier Circuit , 2009 .

[17]  Bhabani Prasad Mandal,et al.  Equivalence Between Two Different Field-Dependent BRST Formulations , 2015, 1503.07390.

[18]  Qingxin Zhu,et al.  Image storage, retrieval, compression and segmentation in a quantum system , 2013, Quantum Inf. Process..

[19]  N. Ranganathan,et al.  Design of Efficient Reversible Binary Subtractors Based on a New Reversible Gate , 2009, 2009 IEEE Computer Society Annual Symposium on VLSI.

[20]  Behjat Forouzandeh,et al.  Quantum Division Circuit Based on Restoring Division Algorithm , 2011, 2011 Eighth International Conference on Information Technology: New Generations.

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

[22]  Nan Jiang,et al.  LSB Based Quantum Image Steganography Algorithm , 2015, International Journal of Theoretical Physics.

[23]  Lijiang Chen,et al.  SQR: a simple quantum representation of infrared images , 2014, Quantum Information Processing.

[24]  Nan Jiang,et al.  Quantum Hilbert Image Scrambling , 2014 .

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

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

[27]  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.

[28]  T. Toffoli,et al.  Conservative logic , 2002, Collision-Based Computing.

[29]  Nan Jiang,et al.  Quantum image scaling using nearest neighbor interpolation , 2015, Quantum Inf. Process..

[30]  Koji Nakamae,et al.  A quantum watermarking scheme using simple and small-scale quantum circuits , 2016, Quantum Information Processing.

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

[32]  Shen Wang,et al.  Quantum realization of the nearest-neighbor interpolation method for FRQI and NEQR , 2016, Quantum Inf. Process..

[33]  Hui Chen,et al.  A watermark strategy for quantum images based on quantum fourier transform , 2012, Quantum Information Processing.

[34]  Ahmed A. Abd El-Latif,et al.  Dynamic watermarking scheme for quantum images based on Hadamard transform , 2014, Multimedia Systems.

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

[36]  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.

[37]  Nan Jiang,et al.  The quantum realization of Arnold and Fibonacci image scrambling , 2014, Quantum Inf. Process..

[38]  Kai Xu,et al.  A novel quantum representation for log-polar images , 2013, Quantum Information Processing.

[39]  Pérès,et al.  Reversible logic and quantum computers. , 1985, Physical review. A, General physics.

[40]  Nan Jiang,et al.  Quantum image scaling up based on nearest-neighbor interpolation with integer scaling ratio , 2015, Quantum Information Processing.