Hilbert space filling curve using scilab

 
 
 
  • Abstract
  • Keywords
  • References
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  • 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.


  • Keywords


    Hilbert Space Filling; Locality Preserving; Scilab Code.

  • References


      [1] Nicholas J. Rose, “Hilbert-Type Space-Filling Curves”

      [2] RevitalDafner, Daniel CohenOr and Yossi Matias, “Context-based Space Filling Curves”, 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 compression”, 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.


 

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Article ID: 9748
 
DOI: 10.14419/ijet.v7i1.9.9748




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