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<p><b>Abstract</b>—A very interesting recent development in data compression is the Burrows-Wheeler Transformation [<ref type="bib" rid="bibT10431">1</ref>]. 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.</p>
Lossless data compression, Burrows-Wheeler Transformation, context trees, suffix trees.
Bernhard Balkenhol, Stefan Kurtz, "Universal Data Compression Based on the Burrows-Wheeler Transformation: Theory and Practice", IEEE Transactions on Computers, vol. 49, no. , pp. 1043-1053, October 2000, doi:10.1109/12.888040
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