Abstract
Text compression algorithms based on the Burrows-Wheeler transform (BWT) typically achieve a good compression ratio but are slow compared to Lempel-Ziv type compression algorithms. The main culprit is the time needed to compute the BWT during compression and its inverse during decompression. We propose to speed up BWT-based compression by performing a grammar-based precompression before the transform. The idea is to reduce the amount of data that BWT and its inverse have to process. We have developed a very fast grammar precompressor using pair replacement. Experiments show a substantial speed up in practice without a significant effect on compression ratio. © 2012 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Kärkkäinen, J., Mikkola, P., & Kempa, D. (2012). Grammar precompression speeds up burrows-wheeler compression. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7608 LNCS, pp. 330–335). Springer Verlag. https://doi.org/10.1007/978-3-642-34109-0_34
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