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Quantum image scaling up based on nearest-neighbor interpolation with integer scaling ratio

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Abstract

Quantum image processing is one of the most active fields in quantum computation and quantum information processing. Some concepts of quantum images and transformations have emerged in recent years. This paper proposes a quantum algorithm to scale up quantum images based on nearest-neighbor interpolation with integer scaling ratio. Firstly, the novel enhanced quantum representation is improved to the generalized quantum image representation to represent a quantum image with arbitrary size \(H \times W\). Then, nearest-neighbor interpolation is used to create new pixels in the enlarged images. Based on them, quantum image scaling up algorithms in the form of circuits are proposed.

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Authors and Affiliations

  1. College of Computer, Beijing University of Technology, Beijing, 100124, China

    Nan Jiang

  2. School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China

    Jian Wang & Yue Mu

Authors
  1. Nan Jiang
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  2. Jian Wang
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  3. Yue Mu
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Corresponding author

Correspondence to Jian Wang.

Additional information

This work is supported by the Fundamental Research Funds for the Central Universities under Grants No. 2015JBM027 and the National Scholarship under Grants Nos. 201406545034 and 201507095087.

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Jiang, N., Wang, J. & Mu, Y. Quantum image scaling up based on nearest-neighbor interpolation with integer scaling ratio. Quantum Inf Process 14, 4001–4026 (2015). https://doi.org/10.1007/s11128-015-1099-5

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  • DOI: https://doi.org/10.1007/s11128-015-1099-5

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