Optimizing run-length algorithm using octonary repetition tree

TL;DR

This paper introduces an octonary repetition tree-based run-length encoding algorithm that significantly improves compression ratios across various data types by addressing duplication issues inherent in traditional RLC methods.

Contribution

It presents the first run-length encoding method with consistently greater than one compression ratio, utilizing ORT to enhance data compression effectiveness.

Findings

Average compression ratio improvement of about 3 times over PRLC1 and PRLC2.

Achieved roughly 2-3 times better compression ratios compared to existing methods.

Applicable to diverse data types including multimedia and documents.

Abstract

Compression is beneficial because it helps detract resource usage. It reduces data storage space as well as transmission traffic and improves web pages loading. Run-length coding (RLC) is a lossless data compression algorithm. Data are stored as a data value and counts. This is useful on data that contains many consecutive runs. This paper proposes a compression algorithm using octonary repetition tree (ORT), based on RLC. ORT is used to overcome the duplication problem in primary RLC algorithms, instead of using flag or codeword. It's the first method of run-length encoding which has the compression ratio greater than one in all tested cases. Experimental results, show average improvement of roughly 3 times, 3 times and 2 times in compression ratio field of study comparing to PRLC1, PRLC2, DF-RLC respectively. By using this approach of run-length encoding we can compress wider types of data, such as multimedia, document, executive files, etc.