License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CPM.2018.3
URN: urn:nbn:de:0030-drops-87049
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/8704/
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Baier, Uwe

On Undetected Redundancy in the Burrows-Wheeler Transform

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LIPIcs-CPM-2018-3.pdf (0.6 MB)

Abstract

The Burrows-Wheeler-Transform (BWT) is an invertible permutation of a text known to be highly compressible but also useful for sequence analysis, what makes the BWT highly attractive for lossless data compression. In this paper, we present a new technique to reduce the size of a BWT using its combinatorial properties, while keeping it invertible. The technique can be applied to any BWT-based compressor, and, as experiments show, is able to reduce the encoding size by 8-16 % on average and up to 33-57 % in the best cases (depending on the BWT-compressor used), making BWT-based compressors competitive or even superior to today's best lossless compressors.

BibTeX - Entry

@InProceedings{baier:LIPIcs:2018:8704,
  author =	{Uwe Baier},
  title =	{{On Undetected Redundancy in the Burrows-Wheeler Transform}},
  booktitle =	{Annual Symposium on Combinatorial Pattern Matching  (CPM 2018)},
  pages =	{3:1--3:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-074-3},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{105},
  editor =	{Gonzalo Navarro and David Sankoff and Binhai Zhu},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2018/8704},
  URN =		{urn:nbn:de:0030-drops-87049},
  doi =		{10.4230/LIPIcs.CPM.2018.3},
  annote =	{Keywords: Lossless data compression, BWT, Tunneling}
}

Keywords: Lossless data compression, BWT, Tunneling
Collection: Annual Symposium on Combinatorial Pattern Matching (CPM 2018)
Issue Date: 2018
Date of publication: 18.05.2018
Supplementary Material: Implementation available at https://github.com/waYne1337/tbwt

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