Universal Data Compression Based on the Burrows-Wheeler Transformation: Theory and Practice

ÐA very interesting recent development in data compression is the Burrows-Wheeler Transformation [1]. The idea is to permute the input sequence in such a way that characters with a similar context are grouped together. We provide a thorough analysis of the Burrows-Wheeler Transformation from an information theoretic point of view. Based on this analysis, the main part of the paper systematically considers techniques to efficiently implement a practical data compression program based on the transformation. We show that our program achieves a better compression rate than other programs that have similar requirements in space and time. Index TermsÐLossless data compression, Burrows-Wheeler Transformation, context trees, suffix trees.