Hilbert space filling curve using scilab

  • Authors

    • Sushma T.V
    • Roopa M
    2018-03-01
    https://doi.org/10.14419/ijet.v7i1.9.9748
  • Hilbert Space Filling, Locality Preserving, Scilab Code.

  • Abstract

    Space filling curve is used widely for linear mapping of multi-dimensional space. This provides a new line of thinking for various applications in image processing, Image compression being the most widely used. The paper highlights the locality preserving property of Hilbert Space filling curve which is essential in numerous applications such asin image compression, numerical analysis of a large aray of data, parallel processing and so on. A simplistic approach forusingHilbert Space filling curve using Scilab code has been presented.

  • References

    1. [1] Nicholas J. Rose, “Hilbert-Type Space-Filling Curvesâ€

      [2] RevitalDafner, Daniel CohenOr and Yossi Matias, “Context-based Space Filling Curvesâ€, EUROGRAPHICS ’2000, Volume 19, 2000

      [3] S. Kamata, R.O.Eason, and E. Kawaguchi. “An implementation of the hilbert scanning algorithm and its application to data compressionâ€, IEICE Transaction information and systems, E-76(4):420–427, April 1993.

      [4] Christo Ananth, Dr.S. Selvakani, K. Vasumathi, “An Efficient Privacy Preservation in Vehicular Communications Using EC-Based Chameleon Hashingâ€, Journal of Advanced Research in Dynamical and Control Systems, 15-Special Issue, December 2017,pp: 787-792.

  • Downloads

  • How to Cite

    T.V, S., & M, R. (2018). Hilbert space filling curve using scilab. International Journal of Engineering & Technology, 7(1.9), 129-131. https://doi.org/10.14419/ijet.v7i1.9.9748

    Received date: 2018-02-26

    Accepted date: 2018-02-26

    Published date: 2018-03-01