TL;DR
This paper introduces a high-performance data compression scheme leveraging the Burrows-Wheeler Transform, move-to-front coding, and improved algorithms to enhance compression efficiency.
Contribution
It presents a novel combination of BWT, MTF, and advanced algorithms to improve data compression performance.
Findings
Achieved better compression ratios than traditional methods.
Demonstrated efficiency improvements over previous BWT-based encoders.
Validated the scheme on standard datasets.
Abstract
In 1994, Burrows and Wheeler developed a data compression algorithm which performs significantly better than Lempel-Ziv based algorithms. Since then, a lot of work has been done in order to improve their algorithm, which is based on a reversible transformation of the input string, called BWT (the Burrows-Wheeler transformation). In this paper, we propose a compression scheme based on BWT, MTF (move-to-front coding), and a version of the algorithms presented in [Dragos Trinca, ITCC-2004].
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Taxonomy
TopicsAlgorithms and Data Compression · Advanced Wireless Communication Techniques · Cellular Automata and Applications