Asymmetric scaling of a quantum image based on bilinear interpolation with arbitrary scaling ratio View Full Text


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Article Info

DATE

2022-07-29

AUTHORS

Chao Gao, Ri-Gui Zhou, Xin Li, Yao-Chong Li

ABSTRACT

As a branch of quantum image processing, the quantum image scaling has been widely studied in the recent years. In this paper, an asymmetric scaling for quantum image with arbitrary scaling ratio is proposed. Firstly, the generalized quantum image representation is employed to represent a quantum image of arbitrary size H×W\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$H \times W$$\end{document}, and the bilinear interpolation is utilized to obtain the interpolated image. Then, the quantum circuit of the quantum image scaling algorithm with different scaling ratios in two dimensions is designed. Finally, the network complexity and simulation results of the two scaling methods are analyzed. The final result shows that the proposed scheme is a quadratic function, which is much lower than the cubic function and exponential function of other bilinear interpolation schemes. More... »

PAGES

270

References to SciGraph publications

  • 2015-01-30. Image segmentation on a quantum computer in QUANTUM INFORMATION PROCESSING
  • 2019-07-17. Quantum image scaling based on bilinear interpolation with arbitrary scaling ratio in QUANTUM INFORMATION PROCESSING
  • 2020-09-12. Asymmetric scaling scheme over the two dimensions of a quantum image in QUANTUM INFORMATION PROCESSING
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  • 2016-12-08. The effects of mixedness and entanglement on the properties of the entropic uncertainty in Heisenberg model with Dzyaloshinski–Moriya interaction in QUANTUM INFORMATION PROCESSING
  • 2014-09-30. Local feature point extraction for quantum images in QUANTUM INFORMATION PROCESSING
  • 2009-07-24. Processing images in entangled quantum systems in QUANTUM INFORMATION PROCESSING
  • 2010-04-17. A flexible representation of quantum images for polynomial preparation, image compression, and processing operations in QUANTUM INFORMATION PROCESSING
  • 2014-09-30. Quantum image scaling using nearest neighbor interpolation in QUANTUM INFORMATION PROCESSING
  • 2015-08-29. Quantum image scaling up based on nearest-neighbor interpolation with integer scaling ratio in QUANTUM INFORMATION PROCESSING
  • 2017-04-28. Quantum arithmetic with the quantum Fourier transform in QUANTUM INFORMATION PROCESSING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11128-022-03612-8

    DOI

    http://dx.doi.org/10.1007/s11128-022-03612-8

    DIMENSIONS

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