Lempel-Ziv Algorithms. LZ77 (Sliding Window). Variants: LZSS (Lempel-Ziv- Storer-Szymanski); Applications: gzip, Squeeze, LHA, PKZIP, ZOO. LZ78 ( Dictionary. version of LZ77, called LZSS, and one improved version of LZ78, called LZW. The base of the LZ77 algorithm is a sliding window technique with two buffers, one. CULZSS algorithm proposed in [7] parallelizes the LZSS algorithm at two levels. The first level is to split the input data into equally sized chunks and each chunk.

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Any failed match results in advancing the compare to the string starting with the next character in the dictionary.

The binary tree may then be used as a search optimization.

Repeat from Step 2, until all the entire input has been decoded. From Wikipedia, the free encyclopedia.

Lempel–Ziv–Storer–Szymanski – Wikipedia

Here is the beginning of Dr. Assuming equal distribution of characters, there’s a 1 in alphabet size chance of characters matching. The source code implementing a hash table search is contained in the version 0. After writing my version 0. Archived on January 10, The rest of this section documents some of what I have tried so far. After implementing string matches with linked listsit seemed like a wasn’t much effort to try matching using hash tables.

It’s modified because of the way my version 0. In my implementation, all pointers list head and next algorithn int indices into the sliding window dictionary. A 16M entry hash table doesn’t strike me as a viable solution. Each version is contained in its own zipped archive which includes the source files and brief instructions for building an executable.

So 18 is the maximum string length encoded by this implementation. This text takes bytes in uncompressed form. For large Nit’s highly unlikely that you’ll ever read an N symbol string that matches the contents of dictionary, so the maximum allowed match length is often limited.

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Allgorithm experimentation and reading, I’ve discovered that the methods used for string matching significantly impact encoding time. This function will read an LZSS encoded input file and write an output file. The sequential search algorithm moves through the dictionary one character at a time, checking for matches to the first character in the string to be encoded.

Uses bitfile library for reading and writing encoded files. However, as Storer and Szymanski observed, it only takes 1 byte to write out characters that match dictionary strings 0 or 1 character long, and 2 bytes to write out characters that match dictionary strings 2 characters long. Information on downloading the lzs code for all of my LZSS implementations may be found here.

LZSS Compression Functions

As stated above, encoded strings are represented as an offset and a length. The additional memory overhead required to implement a binary search tree is one pointer to the root of the tree plus three pointers for each symbol in the sliding window dictionary.

In the examples I have seen, N is typically or and the maximum length allowed for matching strings is typically between 10 and 20 characters. This page was last edited on 21 Marchat Since the minimum encoded length is three, I am able to add three to the 4 bit value stored in the length field, resulting in encoded string lengths of 3 to In my implementation, all pointers hash table and next are int indices into the sliding window dictionary.

Compression formats Compression software codecs.


Linked lists are a natural choice for implementing such dynamic lists. The KMP algorithm requires that the string being searched for be preprocessed.

So, to keep things algorithn, my first implementation used a brute force sequential search to match the string to be encoded to strings in the dictionary.

This function will read lzs input file and write an output file encoded according to the traditional LZSS algorithm. By the time I got around to including it Wikipedia had a reasonable description as well as pseudocode that I could reference. It must be opened.


Corrects an error that occurs when trying to use the default output file for decoding. Algortihm pointers will return an error. However KMP attempts to use some information about the string we’re attempting to find a match for and the comparisons already made in order skip some comparisons that must fail.

I chose characters, because others have achieved good results with dictionaries of this size, and I can encode offsets of 0 to in 12 bits.

Wikipedia provides a description of the algorithm used to insert or remove entries from a binary search tree. Shift a copy of the symbols written to the decoded output into the dictionary. As with everything else that I’ve written, my LZSS implementation lzsd and still leaves room for improvement. If you need to algoritym 9 bits, you might as well have a symbol dictionary so that you can have more entries.

Since the dictionary is a sliding window of the last characters encoded by the algorithm, the lists of strings starting with a given character must be updated as old characters are removed from the dictionary and new characters are added to the dictionary. Unlike the sequential search, when a search fails against a string in a node of a binary tree, the next comparison will start with the string at the root of the subtree that may contain a match.

Additional new symbols cause an equal number of the oldest symbols to slide out. By not encoding strings that offer less than one byte of savings, the minimum encoded length is three characters.