Pipelined decoder for the limited context order Burrows–Wheeler transformation

The Burrows–Wheeler transformation (BWT) is a reversible block sorting transform that is an integral part of many data compression algorithms. This work proposes a memory-efficient pipelined decoder for the BWT. In particular, the authors consider the limited context order BWT that has low memory re...

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Vydané v:	IET circuits, devices & systems Ročník 13; číslo 1; s. 31 - 38
Hlavní autori:	Safieh, Malek, Freudenberger, Jürgen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Stevenage The Institution of Engineering and Technology 01.01.2019 John Wiley & Sons, Inc
Predmet:	Algorithms Burrows-Wheeler transform Coding Context Data compression data compression algorithms Decoding fast encoding fast inverse BWT Field programmable gate arrays inverse transforms limited context order Burrows–Wheeler transformation limited context order BWT decoding memory-efficient pipelined decoder pipelined decoder Research Article reversible block sorting transform sorting Sorting algorithms pipelined decoder data compression memory-efficient pipelined decoder limited context order BWT decoding fast encoding sorting limited context order Burrows–Wheeler transformation reversible block sorting transform inverse transforms data compression algorithms fast inverse BWT decoding
ISSN:	1751-858X, 1751-8598, 1751-8598
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Popis
Shrnutí:	The Burrows–Wheeler transformation (BWT) is a reversible block sorting transform that is an integral part of many data compression algorithms. This work proposes a memory-efficient pipelined decoder for the BWT. In particular, the authors consider the limited context order BWT that has low memory requirements and enable fast encoding. However, the decoding of the limited context order BWT is typically much slower than the encoding. The proposed decoder pipeline provides a fast inverse BWT by splitting the decoding into several processing stages which are executed in parallel.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	1751-858X 1751-8598 1751-8598
DOI:	10.1049/iet-cds.2017.0496