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

Author:

Žalik Borut1ORCID,Strnad Damjan1ORCID,Podgorelec David1ORCID,Kolingerová Ivana2ORCID,Lukač Luka1ORCID,Lukač Niko1ORCID,Kolmanič Simon1ORCID,Žalik Krista1ORCID,Kohek Štefan1ORCID

Affiliation:

1. Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška Cesta 46, SI-2000 Maribor, Slovenia

2. Department of Computer Science and Engineering, University of West Bohemia, Technická 8, 306 14 Plzeň, Czech Republic

Abstract

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.

Funder

Czech Science Foundation

Slovenian Research and Innovation Agency

Publisher

MDPI AG

Subject

General Physics and Astronomy

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