High performance Lempel-Ziv compression using optimized longest string parsing and adaptive Huffman window size

Abstract

Summary form only given. We present optimizations that improve the compression and computational efficiency of Lempel-Ziv (LZ77) and Huffman algorithms. The compression performance of the LZ77 algorithm can be improved by using an optimized longest match parsing strategy. Another factor that can be considered is the size of the reference to the matching string, which can vary due to the secondary Huffman compression. We present an efficient parsing algorithm that considers both factors while minimizing the computational requirements. Our second optimization technique optimizes static Huffman encoding by efficiently dividing the input into blocks of varying size with uneven character frequency distributions.