Entropy (Nov 2023)

A New Transformation Technique for Reducing Information Entropy: A Case Study on Greyscale Raster Images

  • Borut Žalik,
  • Damjan Strnad,
  • David Podgorelec,
  • Ivana Kolingerová,
  • Luka Lukač,
  • Niko Lukač,
  • Simon Kolmanič,
  • Krista Rizman Žalik,
  • Štefan Kohek

DOI
https://doi.org/10.3390/e25121591
Journal volume & issue
Vol. 25, no. 12
p. 1591

Abstract

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This paper proposes a new string transformation technique called Move with Interleaving (MwI). Four possible ways of rearranging 2D raster images into 1D sequences of values are applied, including scan-line, left-right, strip-based, and Hilbert arrangements. Experiments on 32 benchmark greyscale raster images of various resolutions demonstrated that the proposed transformation reduces information entropy to a similar extent as the combination of the Burrows–Wheeler transform followed by the Move-To-Front or the Inversion Frequencies. The proposed transformation MwI yields the best result among all the considered transformations when the Hilbert arrangement is applied.

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