QRCI: A new quantum representation model of color digital images

Abstract In this paper, a new quantum representation model of color digital images (QRCI) is investigated, in which the color information is encoded by the basis states of qubit sequences. QRCI model utilizes 2 n + 6 qubits to store a color digital image with size 2 n × 2 n . Compared with the existing NCQI representation model, the storage capacity of QRCI improves 2 18 times. Moreover, some quantum color image processing operations concerning channels and bit-planes based on QRCI are discussed and their quantum circuits are designed. Comparison results of the quantum circuits indicate that these operations based on QRCI have lower quantum cost than NCQI. Therefore, the new proposed QRCI representation model can save more storage space and it is more convenient to conduct quantum color image processing operations concerning channels and bit-planes. This work will help the researchers to further investigate more complex quantum color image processing operations based on QRCI.

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

[2]  Kai Xu,et al.  Local feature point extraction for quantum images , 2015, Quantum Inf. Process..

[3]  Simona Caraiman,et al.  Quantum Image Filtering in the Frequency Domain , 2013 .

[4]  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.

[5]  Ping Fan,et al.  Quantum multidimensional color image scaling using nearest-neighbor interpolation based on the extension of FRQI , 2017 .

[6]  Ahmed Farouk,et al.  Red-Green-Blue multi-channel quantum representation of digital images , 2017 .

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

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

[9]  I. Chuang,et al.  Quantum Computation and Quantum Information: Bibliography , 2010 .

[10]  Jian Wang,et al.  Quantum image matching , 2016, Quantum Inf. Process..

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

[12]  Fei Yan,et al.  An RGB Multi-Channel Representation for Images on Quantum Computers , 2013, J. Adv. Comput. Intell. Intell. Informatics.

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

[14]  Nan Jiang,et al.  Quantum image scaling up based on nearest-neighbor interpolation with integer scaling ratio , 2015, Quantum Inf. Process..

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

[16]  P. Benioff.  The computer as a physical system: A microscopic quantum mechanical Hamiltonian model of computers as represented by Turing machines , 1980 .

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

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

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

[20]  Qiong Li,et al.  A novel quantum representation of color digital images , 2017, Quantum Inf. Process..

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

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

[23]  Simona Caraiman,et al.  Histogram-based segmentation of quantum images , 2014, Theor. Comput. Sci..

[24]  Salvador E. Venegas-Andraca,et al.  Processing images in entangled quantum systems , 2010, Quantum Inf. Process..

[25]  Ping Fan,et al.  Quantum image Gray-code and bit-plane scrambling , 2015, Quantum Information Processing.

[26]  Kaoru Hirota,et al.  Efficient Color Transformations on Quantum Images , 2011, J. Adv. Comput. Intell. Intell. Informatics.

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

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

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