中国物理B ›› 2023, Vol. 32 ›› Issue (5): 50303-050303.doi: 10.1088/1674-1056/ac8f35

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Quantum color image scaling based on bilinear interpolation

Chao Gao(高超)1,2, Ri-Gui Zhou(周日贵)1,2,†, and Xin Li(李鑫)1,2   

  1. 1 College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China;
    2 Research Center of Intelligent Information Processing and Quantum Intelligent Computing, Shanghai 201306, China
  • 收稿日期:2022-05-12 修回日期:2022-08-14 接受日期:2022-09-05 出版日期:2023-04-21 发布日期:2023-04-26
  • 通讯作者: Ri-Gui Zhou E-mail:rgzhou@shmtu.edu.cn
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No. 6217070290) and Shanghai Science and Technology Project (Grant Nos. 21JC1402800 and 20040501500).

Quantum color image scaling based on bilinear interpolation

Chao Gao(高超)1,2, Ri-Gui Zhou(周日贵)1,2,†, and Xin Li(李鑫)1,2   

  1. 1 College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China;
    2 Research Center of Intelligent Information Processing and Quantum Intelligent Computing, Shanghai 201306, China
  • Received:2022-05-12 Revised:2022-08-14 Accepted:2022-09-05 Online:2023-04-21 Published:2023-04-26
  • Contact: Ri-Gui Zhou E-mail:rgzhou@shmtu.edu.cn
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No. 6217070290) and Shanghai Science and Technology Project (Grant Nos. 21JC1402800 and 20040501500).

摘要: As a part of quantum image processing, quantum image scaling is a significant technology for the development of quantum computation. At present, most of the quantum image scaling schemes are based on grayscale images, with relatively little processing for color images. This paper proposes a quantum color image scaling scheme based on bilinear interpolation, which realizes the $2^{n_{1}}\times 2^{n_{2}}$ quantum color image scaling. Firstly, the improved novel quantum representation of color digital images (INCQI) is employed to represent a $2^{n_{1}}\times 2^{n_{2}}$ quantum color image, and the bilinear interpolation method for calculating pixel values of the interpolated image is presented. Then the quantum color image scaling-up and scaling-down circuits are designed by utilizing a series of quantum modules, and the complexity of the circuits is analyzed. Finally, the experimental simulation results of MATLAB based on the classical computer are given. The ultimate results demonstrate that the complexities of the scaling-up and scaling-down schemes are quadratic and linear, respectively, which are much lower than the cubic function and exponential function of other bilinear interpolation schemes.

关键词: quantum image processing, image scaling, quantum image representation, bilinear interpolation

Abstract: As a part of quantum image processing, quantum image scaling is a significant technology for the development of quantum computation. At present, most of the quantum image scaling schemes are based on grayscale images, with relatively little processing for color images. This paper proposes a quantum color image scaling scheme based on bilinear interpolation, which realizes the $2^{n_{1}}\times 2^{n_{2}}$ quantum color image scaling. Firstly, the improved novel quantum representation of color digital images (INCQI) is employed to represent a $2^{n_{1}}\times 2^{n_{2}}$ quantum color image, and the bilinear interpolation method for calculating pixel values of the interpolated image is presented. Then the quantum color image scaling-up and scaling-down circuits are designed by utilizing a series of quantum modules, and the complexity of the circuits is analyzed. Finally, the experimental simulation results of MATLAB based on the classical computer are given. The ultimate results demonstrate that the complexities of the scaling-up and scaling-down schemes are quadratic and linear, respectively, which are much lower than the cubic function and exponential function of other bilinear interpolation schemes.

Key words: quantum image processing, image scaling, quantum image representation, bilinear interpolation

中图分类号:  (Quantum information)

  • 03.67.-a
03.67.Ac (Quantum algorithms, protocols, and simulations) 03.67.Lx (Quantum computation architectures and implementations) 07.05.Pj (Image processing)