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Lempel-Ziv methods

Lempel-Ziv methods. Dictionary models - I. Dictionary-based compression methods use the principle of replacing substrings in a message with a codeword that identifies each substring in a dictionary , or codebook The dictionary contains a list of substrings and their associated codewords

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Lempel-Ziv methods

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  1. Lempel-Ziv methods

  2. Dictionary models - I • Dictionary-based compression methods use the principle of replacing substrings in a message with a codeword that identifies each substring in a dictionary, or codebook • The dictionary contains a list of substrings and their associated codewords • Unlike symbolwise methods, dictionary methods often use fixed codewords rather than explicit probability distribution Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  3. Dictionary models - II • For example, we can insert into the dictionary the full set of 8-bit ASCII characters How many? and the 256 most common pairs of characters • If we use fixed length codeword, how many bits does we need to index dictionary entries? • SOL. 9 bits • What about the performances in bits/character in the best and in the worst case? • SOL. best:4.5b/char worst:9b/char!! Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  4. Dictionary models - III • Another possibility is to use longer words in the dictionary, perhaps common words like the or and or common components of words like tion. This strings are the phrases of the dictionary • A dictionary with a predefined set of phrases does not achieve good compression • Performances are better if we tune the dictionary on input source, i.e. if we loose input indipendence Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  5. Dictionary models - IV • For istance common phrases for an italian sport newspaper are very rare in a business management book • To avoid the problem of dictionary being unsuitable for the text at hand we can build a new dictionary for each message to be compressed.... • .... but there is a significant overhead for transmitting and storing it • Deciding the size of the dictionary in order to maximize compression is a very difficult problem Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  6. The Lempel-Ziv methods • The only efficient solution to the problem is to use an adaptive dictionary scheme • Pratically all adaptive dictionary compression methods are based on one of the two methods developed by two israely researchers, Abraham Lempel and Jacob Zivin 1977 e 1978, and called LZ77 and LZ78 • "A Universal Algorithm for Sequential Data Compression" in the IEEE Transactions on Information Theory, May 1977 Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  7. The key idea - I • The key insight of the method is that it is possible to automatically build a dictionary of previously seen strings in the text being compressed • The prior text makes a very good dictionary, since it has usually the same style and language of the upcoming text Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  8. The key idea - II • The dictionary does not have to be transmitted with the compressed text, since the decompressor can build it the same way the compressor does • The many variants of Lempel-Ziv methods differ in how pointers are represented and in the limitations on what the pointers are able to refer to • The presence of so many variants is also caused by same patents, and by the disputes over patenting Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  9. The LZ77 family • Quite easy to implement • Fast decoding with little use of memory • The output of the encoding consists of a series of triples • the first component indicates how far back to look in the previously decoded text • the second component is the length of the phrase • the third is next character for the input Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  10. An example - encoding • alphabet {a,b} a b a a b a b aabb <0,0,a> <0,0,b> <2,1,a> <3,2,b> <5,3,b> Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  11. An example - decoding • <0,0,x><0,0,y><2,1,z><2,1,x><5,3,z> <6,3,z><5,2,z> SOL. x y xz xx yxzz xxyz zxz Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  12. A recursive example • <0,0,a><0,0,c><2,1,a><4,2,b><1,10,a> • Despite the recursive references, each character is available when needed a c aa acb ?? bbbbbbbbbba Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  13. Further details on LZ77 • LZ77 algorithm places limitations on how far back a pointer can refer (i.e. on the length of the first component of the triple) and on the maximum size of the string referred to (i.e. on the length of the second component) • For example, in English text there is no gain in using a sliding windows of more than a few thousand characters • We can use a windows of 8.192 characters, i.e. 13 bits Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  14. Further details on LZ77 • At the same time, the length of the match is rarely over 16 characters, so the extra cost to allow longer match usually is not justified • Exercise: encode the sequence 010020$0110$$0111 with a sliding window of 7 symbols and a maximal match length of 3. Calculate the compression ratio SOL.<0,0,0><0,0,1><2,1,0><0,0,2><2,1,$><7,2,1><5,2,$>,<6,3,1> 0000000 0000001 0100100 0000010 0100111 1111001 1011011 1101101 C=(17*2)/7*8=0.607 << 1!!!

  15. LZ77 - encoding • Encode the text S[1..N] using LZ77, with a sliding window of W characters p=1 WHILE p<N { • search for the longest match for S[p...] in S[p-W ... p-1]. Suppose the match occurs at position p-m, with length l • output the triple < p-m, l, S[p+l ] > • p=p + l + 1 } Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  16. LZ77 - decoding • Decode the text S[1..N] using LZ77, with a sliding window of W characters p=1 FOREACH triple < f, l, c> { • S[p ... p + l - 1] = S[ p - f ... p – f + l - 1] Suppose the match occurs at position p-m, with length l • S[p+l ] = c • p=p + l + 1 } Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  17. LZ77 - improvements • The LZ77 has been gradually refined • first component of the triple: it is useful to use variable length, assigning shorter codewords to recent matches (that are more common) • second component of the triple: variable length codes that uses less bits to represent smaller numbers • third component of the triple: in some variants it is added only when needed (when?), with a 1-bit flag to indicate the presence or the absence of this third component Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  18. gzip algorithm - I • gzip is one of the more effective variants of LZ77 • It is distributed by the Gnu Free Software Foundation • home page of gzip project: www.gzip.org Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  19. gzip algorithm - II • gzip uses a hash tables: the next 3 characters to be coded are hashed, and the return value is used as index to lookup a table entry • This entry is the head of a list that contains the places of occurrence of the 3 characters in the window • The list is searched for the longest match • If there is no match the string is coded as raw characters Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  20. gzip algorithm - III • If the match exists, we have a length and a distance, otherwise we have a zero length and a raw character • the sliding window has dimension W=32KB, lengths are limited to 258 bytes • List lengths are limited to avoid time consuming researches • tradeoff accuracy/time  user’s choice Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  21. gzip algorithm - IV • Lengths, distances and raw characters are coded with two Huffman trees, one for distances and the other for lengths and raw characters • Huffman codes are generated processing blocks of up to 64KB (with canonical Huffman) • so gzip it is not really one-pass. From a pratical point of view it is one-pass because blocks are small, so they are read only one time and kept in main memory Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  22. gzip - example abacbcaab <length, distance/character> <0,a><0,b><1,2><0,c><1,3><1,2><1,4><2,7> Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  23. gzip – best compression ...... abcaab abacbcaab <length, distance/character> <0,a><0,b><1,2><0,c><1,3><1,2><1,4><2,7> two solutions • ab + caab • a + bcaab • The first is greedy, it uses longest possible match.But sometimes the second is better. If best compression is selected, gzip takes a longer time but chooses the best of the two, eventually coding raw characters even if matches are possible, if it gives better compression in the long run

  24. LZ78 family • it has restrictions on which substring can be referenced (but this avoids some inefficiency) • decoding is slower than LZ77 and require more memory • does not have a window to limit how far back substring can be referenced • one of its variant, LZW, is widely used in many popular compression systems Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  25. Referentiable strings • The text prior to the current coding position is parsed in substrings, and only parsed phrases can be referenced • Previous phrases are numbered in sequence, and the output is a list of pairs <previous phrase, next character> • This unseen combination is stored as a new phrase Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  26. An example b a a b a b a a a Phrases Output 0 <null> <0,a> <0,b> <1,a> <2,a> <4,a> 1 a 2 b 3 aa 4 ba 5 baa Only this phrases can be referenced • This avoids the inefficiency of having more than one coded representation for the same string, as usual in LZ77

  27. How to store the phrases • It is crucial for algorithm efficiency, to store the phrases in a clever way • This can be obtained using a trie 0 a b Phrases 1 2 0 <null> 1 a a a 2 b 3 4 3 aa a b 4 ba 5 6 5 baa

  28. How to store the phrases • The character of each phrase specify a path from the root to a leaf • The character to be encoded are used to traverse the trie until the path is blocked • The last node contains the phrase number to output • A new node is added with next input character, to form a new phrase 0 a b 1 2 a a 3 4 a b 5 6 b 7 baab <5,b>

  29. A problem • The trie data structure continues to grow during coding, and eventually growth must be stopped to avoid an eccessive use of memory • There are various strategies • the trie can be reinitialized from scratch • the trie can be used as is, without further updates • the trie can be partially rebuild using last part of the text (this avoids the penalties of starting form scratch) Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  30. LZ78 vs. LZ77 • LZ78 encoding can be faster • LZ78 decoding is slower because the decoder must also store the parsed phrases Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  31. LZ78 - exercise • Code the sequence with LZ78 e show the trie that store the phrases 0100101110101001011 • SOL. <0,0><0,1><1,0><2,0><2,1><4,1><1,1><3,1><7,1> 0 0 1 PHRASES 0 <null> 1 0 2 1 3 00 4 10 5 11 6 101 7 01 8 001 9 011 1 2 0 1 0 1 3 7 4 5 1 1 1 8 9 6

  32. LZW variant - I • One of the most popular variants of Lempel-Ziv coding (Welch 1984) • It forms the basis for Unix utility compress and many other popular compressors • The main difference between LZW and LZ78 is that LZW encodes only phrase numbers without any ending characters • This scheme works fine because we initialize the dictionary with a phrase for each character of the source alphabet (e.g. the 256 characters of the 8-bit ASCII) Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  33. LZW variant - II • A new phrase is constructed from a coded one by appending the first character of the next phrase • Suppose we use 7-bit ASCII: dictionary is initialized with 128 phrases (0-127) Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  34. LZW - encoding input: b a ab ab ba aba abaa a output: 97 98 97 128 128 129 131 134 new phrases added 128 ab 129 ba 130 aa 131 aba 132 abb 133 baa 134 abaa Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  35. LZW - decoding input: 97 98 97 128 128 129 131 134 output: a b a ab ab ba aba aba? abaa it is not ready!! ? new phrases added 128 129 130 131 132 133 134 a? ab b? ba aa a? aba ab? ab? abb baa ba? abaa aba? abaa? • The delay in phrase creation is not a problem unless the encoder uses the phrase immediately after its creation. In this case, if decoder inserts the phrases only when they are completed, cannot decode, because it doesn’t have phrase 134

  36. LZW - exercise • Code with LZW the sequence 0102$00$10111$02$ using 8-bit ASCII codes Hint.048, 149, 250, $36 • SOL. 48 49 48 50 36 48 48 36 257 49 265 260 259 PHRASES 256 01 257 10 258 02 259 2$ 260 $0 • 261 00 • 262 0$ • 263 $1 • 264 101 • 265 11 • 11$ 267 $02 268 2$?

  37. Lempel-Ziv methods: summary LZ77 <pointer,length,character> gzip <length, distance/character> LZ78 <phrase,character> LZW <phrase> Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

  38. Lempel-Ziv methods: exercise • Code the message using all studied methods abbb010cac0bb0abb10111b1a using a sliding window of 7 bits and a max match length of 7. No limit is given with respect to the dictionary dimension You can use the following 8-bit ASCII codes a97 b98 c99 048 149 Gabriele Monfardini - Corso di Basi di Dati Multimediali a.a. 2004-2005

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