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LZ78
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. They are both theoretically dictionary coders. LZ77 maintains a sliding window during compression. This was later shown to be equivalent to the ''explicit dictionary'' constructed by LZ78—however, they are only equivalent when the entire data is intended to be decompressed. Since LZ77 encodes and decodes from a sliding window over previously seen characters, decompression must always start at the beginning of the input. Conceptually, LZ78 decompression could allow random access to the input if the entire dictionary were known in ad ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dictionary Coder
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. Methods and applications 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 concordanc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Abraham Lempel
Abraham Lempel ( he, אברהם למפל, born 10 February 1936) is an Israeli computer scientist and one of the fathers of the LZ family of lossless data compression algorithms. Biography Lempel was born on 10 February 1936 in Lwów, Poland (now Lviv, Ukraine). He studied at Technion - Israel Institute of Technology, and received a B.Sc. in 1963, M.Sc. in 1965, and D.Sc. in 1967. Since 1977 he has held the title of full professor. Lempel is now a professor emeritus in Technion. His historically important works start with the presentation of the LZ77 algorithm in a paper entitled "A Universal Algorithm for Sequential Data Compression" in the ''IEEE Transactions on Information Theory'' (May 1977), co-authored by Jacob Ziv. He is the recipient of the 1998 Golden Jubilee Award for Technological Innovation from the IEEE Information Theory Society; and the 2007 IEEE Richard W. Hamming Medal, for "pioneering work in data compression, especially the Lempel-Ziv algorithm". Lempel fo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lempel–Ziv–Welch
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. Algorithm The scenario described by Welch's 1984 paper encodes sequences of 8-bit data as fixed-length 12-bit codes. The codes from 0 to 255 represent 1-character sequences consisting of the corresponding 8-bit character, and the codes 256 through 4095 are created in a dictionary for sequences encountered in the data as it is encoded. At each stage in compression, input bytes are gathered into a sequence until the next character would make a sequence with no code yet in the dictionary. The co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lossless Data Compression
Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved compression rates (and therefore reduced media sizes). By operation of the pigeonhole principle, no lossless compression algorithm can efficiently compress all possible data. For this reason, many different algorithms exist that are designed either with a specific type of input data in mind or with specific assumptions about what kinds of redundancy the uncompressed data are likely to contain. Therefore, compression ratios tend to be stronger on human- and machine-readable documents and code in comparison to entropic binary data (random bytes). Lossless data compression is used in many ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lossless Compression Algorithms
Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved compression rates (and therefore reduced media sizes). By operation of the pigeonhole principle, no lossless compression algorithm can efficiently compress all possible data. For this reason, many different algorithms exist that are designed either with a specific type of input data in mind or with specific assumptions about what kinds of redundancy the uncompressed data are likely to contain. Therefore, compression ratios tend to be stronger on human- and machine-readable documents and code in comparison to entropic binary data (random bytes). Lossless data compression is used in many ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Jacob Ziv
Jacob Ziv ( he, יעקב זיו; born 1931) is an Israeli electrical engineer who, along with Abraham Lempel, developed the LZ family of lossless data compression algorithms. Biography Ziv was born in Tiberias, British mandate Palestine, on 27 November 1931. He received the B.Sc., Dip. Eng., and M.Sc. degrees, all in electrical engineering, from the Technion – Israel Institute of Technology in 1954, and 1957, respectively, and the D.Sc. degree from the Massachusetts Institute of Technology in 1962. Ziv joined the Technion – Israel Institute of Technology in 1970 and is Herman Gross Professor of Electrical Engineering and a Technion Distinguished Professor. His research interests include data compression, information theory, and statistical communication theory. Ziv was Dean of the Faculty of Electrical Engineering from 1974 to 1976 and Vice President for Academic Affairs from 1978 to 1982. Since 1987 Ziv has spent three sabbatical leaves at the Information Research De ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
List Of IEEE Milestones
The following timeline tables list the discoveries and inventions in the history of electrical and electronic engineering. History of discoveries timeline History of associated inventions timeline List of IEEE Milestones The following list of the Institute of Electrical and Electronics Engineers (IEEE) milestones represent key historical achievements in electrical and electronic engineering. Prior to 1870 *1745–1746 – Leyden jar capacitor by Ewald Georg von Kleist and Pieter van Musschenbroek * 1751 – Book '' Experiments and Observations on Electricity'' by Benjamin Franklin * 1757–1775 – Benjamin Franklin's Work in London * 1799 – Alessandro Volta's Electrical Battery Invention * 1836 – Nicholas Callan's Pioneering Contributions to Electrical Science and Technology * 1828–1837 – Pavel Schilling's Pioneering Contribution to Practical Telegraphy * 1838 – Demonstration of Practical Telegraphy * 1852 – Electric Fire Alarm System * 1857 – Heinrich Ge ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Portable Network Graphics
Portable Network Graphics (PNG, officially pronounced , colloquially pronounced ) is a raster-graphics file format that supports lossless data compression. PNG was developed as an improved, non-patented replacement for Graphics Interchange Format (GIF) — unofficially, the initials PNG stood for the recursive acronym "PNG's not GIF". PNG supports palette-based images (with palettes of 24-bit RGB or 32-bit RGBA colors), grayscale images (with or without an alpha channel for transparency), and full-color non-palette-based RGB or RGBA images. The PNG working group designed the format for transferring images on the Internet, not for professional-quality print graphics; therefore non-RGB color spaces such as CMYK are not supported. A PNG file contains a single image in an extensible structure of ''chunks'', encoding the basic pixels and other information such as textual comments and integrity checks documented in RFC 2083. PNG files use the file extension PNG or png and hav ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trie
In computer science, a trie, also called digital tree or prefix tree, is a type of ''k''-ary search tree, a tree data structure used for locating specific keys from within a set. These keys are most often strings, with links between nodes defined not by the entire key, but by individual characters. In order to access a key (to recover its value, change it, or remove it), the trie is traversed depth-first, following the links between nodes, which represent each character in the key. Unlike a binary search tree, nodes in the trie do not store their associated key. Instead, a node's position in the trie defines the key with which it is associated. This distributes the value of each key across the data structure, and means that not every node necessarily has an associated value. All the children of a node have a common prefix of the string associated with that parent node, and the root is associated with the empty string. This task of storing data accessible by its prefix can be ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lempel–Ziv–Stac
Lempel–Ziv–Stac (LZS, or Stac compression or Stacker compression) 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. Standards LZS compression is standardized as an INCITS (previously ANSI) standard. LZS compression is specified for various Internet protocols: * – ''PPP LZS-DCP Compression Protocol (LZS-DCP)'' * – ''PPP Stac LZS Compression Protocol'' * – ''IP Payload Compression Using LZS'' * – ''Transport Layer Security (TLS) Protocol Compression Using Lempel-Ziv-Stac (LZS)'' Algorithm LZS compression and decompression uses an LZ77 type algorithm. It uses the last 2 KB of unc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
