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Quantum realization of the nearest neighbor value interpolation method for INEQR

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Abstract

This paper presents the nearest neighbor value (NNV) interpolation algorithm for the improved novel enhanced quantum representation of digital images (INEQR). It is necessary to use interpolation in image scaling because there is an increase or a decrease in the number of pixels. The difference between the proposed scheme and nearest neighbor interpolation is that the concept applied, to estimate the missing pixel value, is guided by the nearest value rather than the distance. Firstly, a sequence of quantum operations is predefined, such as cyclic shift transformations and the basic arithmetic operations. Then, the feasibility of the nearest neighbor value interpolation method for quantum image of INEQR is proven using the previously designed quantum operations. Furthermore, quantum image scaling algorithm in the form of circuits of the NNV interpolation for INEQR is constructed for the first time. The merit of the proposed INEQR circuit lies in their low complexity, which is achieved by utilizing the unique properties of quantum superposition and entanglement. Finally, simulation-based experimental results involving different classical images and ratios (i.e., conventional or non-quantum) are simulated based on the classical computer’s MATLAB 2014b software, which demonstrates that the proposed interpolation method has higher performances in terms of high resolution compared to the nearest neighbor and bilinear interpolation.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China under Grant Nos. 61463016 and 61763014, Science and technology innovation action plan of Shanghai in 2017 under Grant No.17510740300, Science and technology research project of Jiangxi Provincial Education Department under Grant No. GJJ170382, Project of International Cooperation and Exchanges of Jiangxi Province under Grant No. 20161BBH80034, Project of Humanities and Social Sciences in colleges and universities of Jiangxi Province under Grant No. JC161023.

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Authors and Affiliations

  1. College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China

    RiGui Zhou, WenWen Hu, GaoFeng Luo & XingAo Liu

  2. College of Information Engineering, East China Jiaotong University, Nanchang, 330013, China

    WenWen Hu & Ping Fan

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  1. RiGui Zhou
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Correspondence to WenWen Hu.

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Zhou, R., Hu, W., Luo, G. et al. Quantum realization of the nearest neighbor value interpolation method for INEQR. Quantum Inf Process 17, 166 (2018). https://doi.org/10.1007/s11128-018-1921-y

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