Hilbert space filling curve using scilab

  • Authors

    • Sushma T.V
    • Roopa M
    https://doi.org/10.14419/ijet.v7i1.9.9748

    Received date: February 26, 2018

    Accepted date: February 26, 2018

    Published date: March 1, 2018

  • 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 as in image compression, numerical analysis of a large aray of data, parallel processing and so on. A simplistic approach for using Hilbert Space filling curve using Scilab code has been presented.

  • References

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    3. S. Kamata, R.O.Eason, and E. Kawaguchi. “An implementation of the hilbert scanning algorithm and its application to data com-pression”, 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 Hashing”, Journal of Advanced Research in Dynamical and Control Systems, 15-Special Issue, December 2017,pp: 787-792.
    5. Hui Liu, Tao Cui, Wei Leng and Linbo Zhang, “Encoding and Decoding Algorithms for Arbitrary Dimensional Hilbert Order”, 2016.

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  • How to Cite

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