An Improvement in Lossless Data Compression via Substring Enumeration
Улучшение сжатия данных без потерь посредством перечисления подстрок
2011-05-01
SCID: 54.1/csdje3rj
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BZIP2PPMcompression via substring enumerationlossless data compressionsubstring enumeration
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Abstract (AI)
Dube ´ and Beaudoin proposed a new technique of loss less data compression called compression via sub string enumeration (CSE) in 2010. It has been indicated that the compression ratio of CSE achieves competitive performance for ones of the best PPM variants and BZIP2 from the viewpoint of experimental results. We refine the technique of CSE to reduce the candidate value of range to encode, and make the compression performance of our improvement clear analytically for some input strings, which have zero entropy rate. We show that the performance of compression ratio of the improved CSE never becomes worse than one of the original CSE for any source string in linear-time and linear-space complexity for the length of string.
Key Findings
1
For every source string, the improved CSE’s compression ratio is never worse than that of original CSE.
2
Original CSE had experimentally demonstrated compression ratios competitive with strong PPM variants and BZIP2 benchmarks.
3
The improved CSE enables analytical clarification of compression performance for some input strings with zero entropy rate.
4
The improved method operates with linear-time and linear-space complexity relative to the input string length.
5
The study refines compression via substring enumeration (CSE) by reducing the candidate range of values used for encoding.
Research Object
lossless data compression via substring enumeration (CSE) for source strings
Research Subject
the improved CSE’s compression-ratio performance, candidate-range reduction, and linear-time/linear-space guarantees, including for zero-entropy-rate strings
Publication Details
Publication Date
2011-05-01
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