Block sorting and compression

Arnavut, Ziya; Magliveras, Spyros S.

doi:10.1109/dcc.1997.582009

Cited by 25 publications

(26 citation statements)

References 4 publications

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“…Stable sorting reserves the order of the same symbols. If we represent the sorted version of y [1, n] by z[1, n], we have Then, we write for the symbol y i if it appears as the jth symbol z j in z[1, n] [6]. In the present example, we have S1 5, S2 6, S3 7, and so on.…”

Section: Block-sorting Data Compressionmentioning

confidence: 94%

Notes on block-sorting data compression

Yokoo

1999

Electron. Comm. Jpn. Pt. III

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The block-sorting data compression method of Burrows and Wheeler has received considerable attention in anticipation that it may be comparable, or even superior, to the ZivLempel codes. This article discusses its characteristic points from the viewpoint of string algorithms. The block-sorting compression algorithm initially sorts all rotations of an input text lexicographically. This transformation is still reversible when we restrict the key length of sorting. We first focus on the combinatorial aspect of this reversibility, then show that the block-sorting algorithm has the capability of finding repetitions in an original string. We give a new description of the algorithm in terms of the KarpMillerRosenberg (KMR) repetition finder in order to combine the above two aspects.

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Section: Block-sorting Data Compressionmentioning

confidence: 94%

Notes on block-sorting data compression

Yokoo

1999

Electron. Comm. Jpn. Pt. III

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“…These claims are supported by experience. Arnavut and Magliveras 14 have shown that the Burrows-Wheeler Transform is but one of a group of permutations, and that it may be possible to select a permutation group with better compression and accompany the compressed data with an ordinal group index or a coding of the permutation itself.…”

Section: Block Sorting or Burrows-wheeler Transformmentioning

confidence: 99%

Symbol ranking text compressors: review and implementation

Fenwick

1998

Softw: Pract. Exper.

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SUMMARY Methods used by Shannon in 1951 when investigating the information content of English text areshown to lead to a class of 'symbol ranking' text compressors. Included in this class are some recent compressors which combine high performance with completely novel techniques. These are described under the aegis of the symbol ranking classification. Some new compressors, deliberately designed as symbol ranking, are then described. One of these has operated at over 1 Mbyte per second in software, and should be suitable for hardware implementation at tens of megabytes per second, or higher.

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“…Itoh und Tanaka entwickelten 1999 ein neues Verfahren -das sogenannte "Two Stage Suffix Sort" - [12], welches von Kao im Rahmen einer Dissertation aufgegriffen und speziell für Folgen von sich wiederholenden Zeichen optimiert wurde [13].Auch die der Burrows-WheelerTransformation nachgeordneten Stufen sind Gegenstand zahlreicher Untersuchungen gewesen. Hierzu zählen insbesondere die Erweiterungen von Arnavut and Magliveras aus dem Jahre 1997 [2], von Balkenhol und Shtarkov aus dem Jahre 1999 [4], von Deorowicz aus dem Jahre 2000 [8] und 2002 [9] sowie von Abel aus dem Jahre 2003 [1].…”

Section: Einführungunclassified

“…Hierbei besteht die GST aus zwei Unterstufen, die in Abb. 2 hand der Zeichenfolge ABRAKADABRAABRAKADABRAAB-RAKADABRA verdeutlicht. Zur besserenÜbersicht werden die Ein-und Ausgabedaten der Stufen in Abb.…”

Section: Der Aufbau Der Erweiterten Varianteunclassified

Grundlagen des Burrows-Wheeler-Kompressionsalgorithmus

Abel

2004

Informatik - Forschung und Entwicklung

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Zusammenfassung. Der Burrows-Wheeler-Kompressionsalgorithmus hat als ein universelles Kompressionsverfahren in den letzten Jahren aufgrund seiner hervorragenden Kompressionsraten und hohen Verarbeitungsgeschwindigkeiten eine bemerkenswerte Beachtung erfahren. Das Herzstück des Algorithmus stellt die sogenannte Burrows-WheelerTransformation dar. Es handelt sich bei dieser Transformation um eine Permutation der Eingabedaten, welche Zeichen mitähnlichem Kontext nahe beieinander anordnet. Die Transformation sowie die zugehörige Rücktransformation werden zusammen mit den weiteren Stufen des Algorithmus in einer gegenüber der Standardversion verbesserten Variante vorgestellt und die Ergebnisse mit denen anderer Datenkompressionsalgorithmen verglichen.Abstract. The Burrows-Wheeler Compression Algorithm as a universal compression scheme has received considerable attention over recent years for both outstanding compression rates and high speed. The Burrows-Wheeler transform represents the heart of such an algorithm. The transform is a permutation of the input sequence, which sorts symbols with similar contexts close together. The transform and the corresponding inverse transform together with further stages of the algorithm will be presented on the example of an improved version. The results of this algorithm will be compared to the results of other compression algorithms.

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Block sorting and compression

Cited by 25 publications

References 4 publications

Notes on block-sorting data compression

Notes on block-sorting data compression

Symbol ranking text compressors: review and implementation

Grundlagen des Burrows-Wheeler-Kompressionsalgorithmus

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