EAH: A New Encoder based on Adaptive Variable-length Codes

TL;DR

This paper introduces EAH, an improved adaptive variable-length coding algorithm that enhances data compression by generalizing previous methods, analyzing entropy bounds, and implementing parallel processing for efficiency.

Contribution

It proposes the EAHn algorithm, extends previous adaptive coding methods, and provides entropy analysis, implementation details, experimental results, and a parallel version.

Findings

EAHn outperforms previous adaptive coding algorithms.

Entropy bounds for EAHn are established.

Parallel EAHn achieves improved computational efficiency.

Abstract

Adaptive variable-length codes associate a variable-length codeword to the symbol being encoded depending on the previous symbols in the input string. This class of codes has been recently presented in [Dragos Trinca, arXiv:cs.DS/0505007] as a new class of non-standard variable-length codes. New algorithms for data compression, based on adaptive variable-length codes of order one and Huffman's algorithm, have been recently presented in [Dragos Trinca, ITCC 2004]. In this paper, we extend the work done so far by the following contributions: first, we propose an improved generalization of these algorithms, called EAHn. Second, we compute the entropy bounds for EAHn, using the well-known bounds for Huffman's algorithm. Third, we discuss implementation details and give reports of experimental results obtained on some well-known corpora. Finally, we describe a parallel version of EAHn using the PRAM model of computation.