A pseudo color coding method for quantum image

doi:10.3969/j.issn.1007-5461.2022.03.006

Abstract

Abstract: In order to solve the problem of image enhancement in quantum image processing, a quantum image pseudo color coding method based on gray level-color transformation method is proposed. Based on the generalized quantum image representation (GQIR) model, the hot metal code segment function is quantized, and the quantum circuit diagram of the algorithm is given. The quantum circuit design is divided into three parts: quantum R converter, quantum G converter and quantum B converter, and the number of basic quantum gates used in the total quantum circuit diagram is 2947. Compared with classical pseudo color coding, quantum image pseudo color coding is based on the superposition and coherence of quantum states, which can reduce the spatial and temporal complexity exponentially. The simulation results show that the algorithm is feasible.

Key words: image processing, quantum image pseudo-color coding, gray level-color transformation method, piecewise function of hot metal code

CLC Number:

TP391

ZANG Yiming, ZHU Shangchao, WEI Zhanhong∗, LIU Zhifei, LIN Xiaozhu, SUN Wentao. A pseudo color coding method for quantum image[J]. Chinese Journal of Quantum Electronics, 2022, 39(3): 343-353.

References

[1]Deutsch, D.Quantum theory,the Church-Turing principle and the universal quantum computer[J].Proceedings of the Royal Society of London, 1985, 400(1818):97-117
[2]Venegas-Andraca S. E., Bose S.Storing, processing and retrieving an image using quantum mechanics[J].Proceedings of the SPIE Conference on Quantum, Information and Computation, 2003, :137-147
[3]Latorre J I.Image compression and entanglement[J].Computer Science, 2005, :-
[4]Venegas-Andraca S.E.,Ball J LProcessing images in entangled quantum systems[J].Quantum Information Processing, 2010, 9(1):1-11
[5]Le P.Q.,Dong F,Hirota KA flexible representation of quantum images for polynomial preparation,image compression,and processing operations[J].Quantum Information Processing, 2011, 10(1):63-84
[6]Zhang Y, Lu K, GaoY H, et al.NEQR: a novel enhanced quantum representation of digital images[J].Quantum Information Processing, 2013, 12(12):2833-2860
[7]Sun B, lliyasu A M, Yan F, et al.An RGB multi-channel representation for images on quantum computers[J].Journal of Advanced Computational Intelligence and Intelligent Infonmatics, 2013, 17(3):404-417
[8]Zhang Y, Lu K, Gao Y, et al.A novel quantum representation for log-polar images[J].Quantum Information Processing, 2013, 12(9):3103-3126
[9]Li H, Zhu O, Lan S, et al.Image storage,retrieval,compression and segmentation in a quantum system[J].Quantum Information Processing, 2013, 12(6):2269-2290
[10]Li H S, Zhu O, Zhou R G, et al.Multi-dimensional color image storage and retrieval for a normal arbitrary quantum superposition state[J].Quantum Information Processing, 2014, 13(4):991-1011
[11]Nan J, Wu W, Luo W, et al.Quantum image pseudocolor coding based on the density-stratified method[J].Quantum Information Processing, 2015, 14(5):1735-1755
[12]Sang J, Wang S, Li Q.A novel quantum representation of color digital images[J].Quantum Information Processing, 2017, 16(2):42-
[13]Li H S, Chen X, Xia H Y, et al.A Quantum Image Representation Based on Bitplanes[J].IEEE Access, 2018, 6:62396-62404
[14]Le P.Q.,lliyasu A M,Dong F,et alFast geometric transformations on quantum images[J].Iaeng International Journal of Applied Mathematics, 2010, 40(3):113-123
[15]Jiang N, Wang L.Quantum image scaling using nearest neighbor interpolation[J].Quantum Information Processing, 2015, 14(5):1559-1571
[16]Jian, Wang, Nan, et al.Quantum image translation[J].Quantum Information Processing, 2015, 14(5):1589-1604
[17]Zhou R G, Hu W, Fan P, et al.Quantum realization of the bilinear interpolation method for NEQR[J].Scientific Reports, 2017, 7(1):2511-
[18]Caraiman S, Manta V I.Image segmentation on a quantum computer[J].Quantum Information Processing, 2015, 14(5):1693-1715
[19]Zhang Y, Lu K, Xu K, et al.Local feature point extraction for quantum images[J].Quantum Information Processing, 2015, 14(5):1573-1588
[20]Jiang N, Ji Z, Li H, et al.Quantum image interest point extraction[J].Modern Physics Letters A, 2021, :-
[21]Zhang W W, Gao F, Liu B, et al.A watermark strategy for quantum images based on quantum Fourier transform[J].Quantum Information Processing, 2013, 12(4):793-803
[22]Jiang N, Wang L, Wu W Y.Quantum Hilbert image scrambling[J].International Journal of Theoretical Physics, 2014, 53(7):2463-2484
[23]Hou C, Liu X, Feng S.Quantum image scrambling algorithm based on discrete Baker map[J].Modern Physics Letters A, 2020, :2050145-2050145
[24]Zhou R G, Chang Z B, Fan P, et al.Quantum Image Morphology Processing Based on Quantum Set Operation[J].International Journal of Theoretical Physics, 2015, 54(6):1974-1986
[25]Yuan S, Mao X, Chen L, et al.Improved quantum dilation and erosion operations[J].International Journal of Quantum Information, 2016, 14(07):1650036-
[26]Fan P, Zhou R G, Hu W W, et al.Quantum Circuit Realization of Morphological Gradient for Quantum Grayscale Image[J].International Journal of Theoretical Physics, 2019, 58(2):415-435
[27]Li Yida.Digital logic circuit design and implementation[M]. Beijing: Science press, 2004, 97-102 (in Chinese).
[28]李宜达.数字逻辑电路设计与实现[M]. 北京: 科学出版社, 2004, 97-102.