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Author Manzini, Giovanni
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2001
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Burrows—Wheeler transform ♦ Block sorting ♦ Move-to-front encoding ♦ Worst-case analysis of compression
Abstract The Burrows—Wheeler Transform (also known as Block-Sorting) is at the base of compression algorithms that are the state of the art in lossless data compression. In this paper, we analyze two algorithms that use this technique. The first one is the original algorithm described by Burrows and Wheeler, which, despite its simplicity outperforms the Gzip compressor. The second one uses an additional run-length encoding step to improve compression. We prove that the compression ratio of both algorithms can be bounded in terms of the $\textit{k}th$ order empirical entropy of the input string for any $\textit{k}$ ≥ 0. We make no assumptions on the input and we obtain bounds which hold in the worst case that is for every possible input string. All previous results for Block-Sorting algorithms were concerned with the average compression ratio and have been established assuming that the input comes from a finite-order Markov source.
ISSN 00045411
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2001-05-01
Publisher Place New York
e-ISSN 1557735X
Journal Journal of the ACM (JACM)
Volume Number 48
Issue Number 3
Page Count 24
Starting Page 407
Ending Page 430


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Source: ACM Digital Library