Data Compression/grammar-based compression
grammar-based compression
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Grammar-based compression was proposed in 2000.[1]
Several data compression methods can be viewed as grammar-based compression:
- The Sequitur data compression algorithm uses a context-free grammar to represent a string such as a data file. It is relatively fast (linear-time encoding and linear-time decoding).[2]
- Longest Match
- Most frequent digram
- The Sequential data compression algorithm is an improvement on Sequitur.[3]
- Although it pre-dates grammar-based compression, LZ78 and LZW (but not LZ77) can be interpreted as a kind of grammar.[3]
- It has been shown that "a structured grammar" gives better compression than "an irreducible grammar".[4]
When the output of the grammar transform is compressed with a zero-order entropy coder (such as a zero-order arithmetic coder), grammar compression outperforms the Unix Compress and Gzip algorithms.[1]
The Re-Pair algorithm is a grammar based compression algorithm. Its decoder operates as follows:[5]
FIXME: fill in details.
Further reading
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- ↑ a b En-hui Yang and John C. Kieffer. "Efficient Universal Lossless Data Compression Algorithms Based on a Greedy Sequential Grammar Transform—Part One: Without Context Models". 2000.
- ↑ Richard Ladner. "Sequitur" p. 56. 2007.
- ↑ a b Eric Lehman and Abhi Shelat. "Approximation Algorithms for Grammar-Based Compression". "Approximation Algorithms for Grammar-Based Compression". 2002.
- ↑ John Kieffer and En-hui Yang. "Structured grammar-based codes for universal lossless data compression". 2002.
- ↑ Matej Mežik. "Compression Using Context Free Grammars". 2011.
- Re-Store is a phrase browsing system based on the Re-Pair compression algorithm.[1]
- ↑ Wan, R., Re-Store Software, archived from the original on 2015-07-21