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Multivalued Discrete Tomography Using Dynamical System That Describes Competition

Author

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  • Takeshi Kojima
  • Tetsushi Ueta
  • Tetsuya Yoshinaga

Abstract

Multivalued discrete tomography involves reconstructing images composed of three or more gray levels from projections. We propose a method based on the continuous-time optimization approach with a nonlinear dynamical system that effectively utilizes competition dynamics to solve the problem of multivalued discrete tomography. We perform theoretical analysis to understand how the system obtains the desired multivalued reconstructed image. Numerical experiments illustrate that the proposed method also works well when the number of pixels is comparatively high even if the exact labels are unknown.

Suggested Citation

  • Takeshi Kojima & Tetsushi Ueta & Tetsuya Yoshinaga, 2017. "Multivalued Discrete Tomography Using Dynamical System That Describes Competition," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-9, November.
    • Handle: RePEc:hin:jnlmpe:8160354
    DOI: 10.1155/2017/8160354
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