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A dictionary coder, also sometimes known as a substitution coder, is a class of lossless data compression algorithms which operate by searching for matches between the text to be compressed and a set of strings contained in a data structure (called the 'dictionary') maintained by the encoder. When the encoder finds such a match, it substitutes a reference to the string's position in the data structure.
Some dictionary coders use a 'static dictionary', one whose full set of strings is determined before coding begins and does not change during the coding process. This approach is most often used when the message or set of messages to be encoded is fixed and large; for instance, an application that stores the contents of a book in the limited storage space of a PDA generally builds a static dictionary from a concordance of the text and then uses that dictionary to compress the verses. This scheme of using Huffman coding to represent indices into a concordance has been called "Huffword". [1]
In a related and more general method, a dictionary is built from redundancy extracted from a data environment (various input streams) which dictionary is then used statically to compress a further input stream. For example, a dictionary is built from old English texts then is used to compress a book. [2]
More common are methods where the dictionary starts in some predetermined state but the contents change during the encoding process, based on the data that has already been encoded. Both the LZ77 and LZ78 algorithms work on this principle. In LZ77, a circular buffer called the "sliding window" holds the last N bytes of data processed. This window serves as the dictionary, effectively storing every substring that has appeared in the past N bytes as dictionary entries. Instead of a single index identifying a dictionary entry, two values are needed: the length, indicating the length of the matched text, and the offset (also called the distance), indicating that the match is found in the sliding window starting offset bytes before the current text.
LZ78 uses a more explicit dictionary structure; at the beginning of the encoding process, the dictionary is empty. An index value of zero is used to represent the end of a string, so the first index of the dictionary is one. At each step of the encoding process, if there is no match, then the last matching index (or zero) and character are both added to the dictionary and output to the compressed stream. If there is a match, then the working index is updated to the matching index, and nothing is output.
LZW is similar to LZ78, but, the dictionary is initialized to all possible symbols. The typical implementation works with 8 bit symbols, so the dictionary "codes" for hex 00 to hex FF (decimal 255) are pre-defined. Dictionary entries would be added starting with code value hex 100. Unlike LZ78, if a match is not found (or if the end of data), then only the dictionary code is output. This creates a potential issue since the decoder output is one step behind the dictionary. Refer to LZW for how this is handled. Enhancements to LZW include handing symbol sizes other than 8 bits and having reserved codes to reset the dictionary and to indicate end of data.
The Graphics Interchange Format is a bitmap image format that was developed by a team at the online services provider CompuServe led by American computer scientist Steve Wilhite on June 15, 1987. It has since come into widespread usage on the World Wide Web due to its wide support and portability between applications and operating systems.
Lossless compression is a class of data compression algorithms that allows the original data to be perfectly reconstructed from the compressed data. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved compression rates.
bzip2 is a free and open-source file compression program that uses the Burrows–Wheeler algorithm. It only compresses single files and is not a file archiver. It is developed by Julian Seward and maintained by Federico Mena. Seward made the first public release of bzip2, version 0.15, in July 1996. The compressor's stability and popularity grew over the next several years, and Seward released version 1.0 in late 2000. Following a nine year hiatus of updates for the project since 2010, on June 4, 2019 Federico Mena accepted maintainership of the bzip2 project.
Lempel–Ziv–Welch (LZW) is a universal lossless data compression algorithm created by Abraham Lempel, Jacob Ziv, and Terry Welch. It was published by Welch in 1984 as an improved implementation of the LZ78 algorithm published by Lempel and Ziv in 1978. The algorithm is simple to implement and has the potential for very high throughput in hardware implementations. It is the algorithm of the widely used Unix file compression utility compress and is used in the GIF image format.
LZ77 and LZ78 are the two lossless data compression algorithms published in papers by Abraham Lempel and Jacob Ziv in 1977 and 1978. They are also known as LZ1 and LZ2 respectively. These two algorithms form the basis for many variations including LZW, LZSS, LZMA and others. Besides their academic influence, these algorithms formed the basis of several ubiquitous compression schemes, including GIF and the DEFLATE algorithm used in PNG and ZIP.
In computing, Deflate is a lossless data compression file format that uses a combination of LZSS and Huffman coding. It was designed by Phil Katz, for version 2 of his PKZIP archiving tool. Deflate was later specified in RFC 1951 (1996).
The Lempel–Ziv–Markov chain algorithm (LZMA) is an algorithm used to perform lossless data compression. It has been under development since either 1996 or 1998 by Igor Pavlov and was first used in the 7z format of the 7-Zip archiver. This algorithm uses a dictionary compression scheme somewhat similar to the LZ77 algorithm published by Abraham Lempel and Jacob Ziv in 1977 and features a high compression ratio and a variable compression-dictionary size, while still maintaining decompression speed similar to other commonly used compression algorithms.
7z is a compressed archive file format that supports several different data compression, encryption and pre-processing algorithms. The 7z format initially appeared as implemented by the 7-Zip archiver. The 7-Zip program is publicly available under the terms of the GNU Lesser General Public License. The LZMA SDK 4.62 was placed in the public domain in December 2008. The latest stable version of 7-Zip and LZMA SDK is version 19.00.
Adaptive coding refers to variants of entropy encoding methods of lossless data compression. They are particularly suited to streaming data, as they adapt to localized changes in the characteristics of the data, and don't require a first pass over the data to calculate a probability model. The cost paid for these advantages is that the encoder and decoder must be more complex to keep their states synchronized, and more computational power is needed to keep adapting the encoder/decoder state.
Prediction by partial matching (PPM) is an adaptive statistical data compression technique based on context modeling and prediction. PPM models use a set of previous symbols in the uncompressed symbol stream to predict the next symbol in the stream. PPM algorithms can also be used to cluster data into predicted groupings in cluster analysis.
rzip is a huge-scale data compression computer program designed around initial LZ77-style string matching on a 900 MB dictionary window, followed by bzip2-based Burrows–Wheeler transform and entropy coding (Huffman) on 900 kB output chunks.
LHA or LZH is a freeware compression utility and associated file format. It was created in 1988 by Haruyasu Yoshizaki, and originally named LHarc. A complete rewrite of LHarc, tentatively named LHx, was eventually released as LH. It was then renamed to LHA to avoid conflicting with the then-new MS-DOS 5.0 LH command. According to early documentation, LHA is pronounced like La.
The move-to-front (MTF) transform is an encoding of data designed to improve the performance of entropy encoding techniques of compression. When efficiently implemented, it is fast enough that its benefits usually justify including it as an extra step in data compression algorithms.
Snappy is a fast data compression and decompression library written in C++ by Google based on ideas from LZ77 and open-sourced in 2011. It does not aim for maximum compression, or compatibility with any other compression library; instead, it aims for very high speeds and reasonable compression. Compression speed is 250 MB/s and decompression speed is 500 MB/s using a single core of a circa 2011 "Westmere" 2.26 GHz Core i7 processor running in 64-bit mode. The compression ratio is 20–100% lower than gzip.
Lempel–Ziv–Storer–Szymanski (LZSS) is a lossless data compression algorithm, a derivative of LZ77, that was created in 1982 by James Storer and Thomas Szymanski. LZSS was described in article "Data compression via textual substitution" published in Journal of the ACM.
HTTP compression is a capability that can be built into web servers and web clients to improve transfer speed and bandwidth utilization.
In computer science, compressed pattern matching is the process of searching for patterns in compressed data with little or no decompression. Searching in a compressed string is faster than searching an uncompressed string and requires less space.
ZPAQ is an open source command line archiver for Windows and Linux. It uses a journaling or append-only format which can be rolled back to an earlier state to retrieve older versions of files and directories. It supports fast incremental update by adding only files whose last-modified date has changed since the previous update. It compresses using deduplication and several algorithms depending on the data type and the selected compression level. To preserve forward and backward compatibility between versions as the compression algorithm is improved, it stores the decompression algorithm in the archive. The ZPAQ source code includes a public domain API, libzpaq, which provides compression and decompression services to C++ applications. The format is believed to be unencumbered by patents.
Lempel–Ziv–Stac is a lossless data compression algorithm that uses a combination of the LZ77 sliding-window compression algorithm and fixed Huffman coding. It was originally developed by Stac Electronics for tape compression, and subsequently adapted for hard disk compression and sold as the Stacker disk compression software. It was later specified as a compression algorithm for various network protocols. LZS is specified in the Cisco IOS stack.
liblzg is a compression library for performing lossless data compression. It implements an algorithm that is a variation of the LZ77 algorithm, called the LZG algorithm, with the primary focus of providing a very simple and fast decoding method. One of the key features of the algorithm is that it requires no memory during decompression. The software library is free software, distributed under the zlib license.