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作 者:高超 周日贵 李鑫 Chao Gao;Ri-Gui Zhou;Xin Li(College of Information Engineering,Shanghai Maritime University,Shanghai 201306,China;Research Center of Intelligent Information Processing and Quantum Intelligent Computing,Shanghai 201306,China)
机构地区:[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
出 处:《Chinese Physics B》2023年第5期235-244,共10页中国物理B(英文版)
基 金:the National Natural Science Foundation of China (Grant No. 6217070290);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)) × 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)) × 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
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