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

Authors :
Borut Žalik
Damjan Strnad
David Podgorelec
Ivana Kolingerová
Luka Lukač
Niko Lukač
Simon Kolmanič
Krista Rizman Žalik
Štefan Kohek
Source :
Entropy, Vol 25, Iss 12, p 1591 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

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.

Details

Language :
English
ISSN :
10994300
Volume :
25
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Entropy
Publication Type :
Academic Journal
Accession number :
edsdoj.6eea304f0a0b4f3886145ecdf7b9df3f
Document Type :
article
Full Text :
https://doi.org/10.3390/e25121591