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Lossless
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 ...
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TIFF
Tag Image File Format, abbreviated TIFF or TIF, is an image file format for storing raster graphics images, popular among graphic artists, the publishing industry, and photographers. TIFF is widely supported by scanning, faxing, word processing, optical character recognition, image manipulation, desktop publishing, and page-layout applications. The format was created by the Aldus Corporation for use in desktop publishing. It published the latest version 6.0 in 1992, subsequently updated with an Adobe Systems copyright after the latter acquired Aldus in 1994. Several Aldus or Adobe technical notes have been published with minor extensions to the format, and several specifications have been based on TIFF 6.0, including TIFF/EP (ISO 12234-2), TIFF/IT (ISO 12639), TIFF-F (RFC 2306) and TIFF-FX (RFC 3949). History TIFF was created as an attempt to get desktop scanner vendors of the mid-1980s to agree on a common scanned image file format, in place of a multitude of proprietary for ...
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Video Compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding; encoding done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a signal. C ...
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Data Compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding; encoding done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a signal. ...
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Lossy Compression
In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. The different versions of the photo of the cat on this page show how higher degrees of approximation create coarser images as more details are removed. This is opposed to lossless data compression (reversible data compression) which does not degrade the data. The amount of data reduction possible using lossy compression is much higher than using lossless techniques. Well-designed lossy compression technology often reduces file sizes significantly before degradation is noticed by the end-user. Even when noticeable by the user, further data reduction may be desirable (e.g., for real-time communication or to reduce transmission times or storage needs). The most widely used lossy compression al ...
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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 ...
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Bit Rate
In telecommunications and computing, bit rate (bitrate or as a variable ''R'') is the number of bits that are conveyed or processed per unit of time. The bit rate is expressed in the unit bit per second (symbol: bit/s), often in conjunction with an SI prefix such as kilo (1 kbit/s = 1,000 bit/s), mega (1 Mbit/s = 1,000 kbit/s), giga (1 Gbit/s = 1,000 Mbit/s) or tera (1 Tbit/s = 1,000 Gbit/s). The non-standard abbreviation bps is often used to replace the standard symbol bit/s, so that, for example, 1 Mbps is used to mean one million bits per second. In most computing and digital communication environments, one byte per second (symbol: B/s) corresponds to 8 bit/s. Prefixes When quantifying large or small bit rates, SI prefixes (also known as metric prefixes or decimal prefixes) are used, thus: Binary prefixes are sometimes used for bit rates. The International Standard ( IEC 80000-13) specifies different a ...
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JPEG2000
JPEG 2000 (JP2) is an image compression standard and coding system. It was developed from 1997 to 2000 by a Joint Photographic Experts Group committee chaired by Touradj Ebrahimi (later the JPEG president), with the intention of superseding their original JPEG standard (created in 1992), which is based on a discrete cosine transform (DCT), with a newly designed, wavelet-based method. The standardized filename extension is .jp2 for ISO/IEC 15444-1 conforming files and .jpx for the extended part-2 specifications, published as ISO/IEC 15444-2. The registered MIME types are defined in RFC 3745. For ISO/IEC 15444-1 it is image/jp2. JPEG 2000 code streams are regions of interest that offer several mechanisms to support spatial random access or region of interest access at varying degrees of granularity. It is possible to store different parts of the same picture using different quality. JPEG 2000 is a compression standard based on a discrete wavelet transform (DWT). The standard cou ...
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Huffman Coding
In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression. The process of finding or using such a code proceeds by means of Huffman coding, an algorithm developed by David A. Huffman while he was a Sc.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes". The output from Huffman's algorithm can be viewed as a variable-length code table for encoding a source symbol (such as a character in a file). The algorithm derives this table from the estimated probability or frequency of occurrence (''weight'') for each possible value of the source symbol. As in other entropy encoding methods, more common symbols are generally represented using fewer bits than less common symbols. Huffman's method can be efficiently implemented, finding a code in time linear to the number of input weights if these weights are sorted. However, although opt ...
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LZ77 And LZ78 (algorithms)
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 ...
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Joint Encoding
In audio engineering, joint encoding refers to a joining of several channels of similar information during encoding in order to obtain higher quality, a smaller file size, or both. Joint stereo The term joint stereo has become prominent as the Internet has allowed for the transfer of relatively low bit rate, acceptable-quality audio with modest Internet access speeds. Joint stereo refers to any number of encoding techniques used for this purpose. Two forms are described here, both of which are implemented in various ways with different codecs, such as MP3, Advanced Audio Coding, AAC and Ogg Vorbis. Intensity stereo coding This form of joint stereo uses a technique known as joint frequency encoding, which functions on the principle of sound localization. Human hearing is predominantly less acute at perceiving the direction of certain audio frequencies. By exploiting this characteristic, intensity stereo coding can reduce the data rate of an audio stream with little or no perceived ...
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Asymmetric Numeral Systems
Asymmetric numeral systems (ANS)J. Duda, K. Tahboub, N. J. Gadil, E. J. Delp''The use of asymmetric numeral systems as an accurate replacement for Huffman coding'' Picture Coding Symposium, 2015.J. Duda''Asymmetric numeral systems: entropy coding combining speed of Huffman coding with compression rate of arithmetic coding'' arXiv:1311.2540, 2013. is a family of entropy encoding methods introduced by Jarosław (Jarek) Duda from Jagiellonian University, used in data compression since 2014 due to improved performance compared to previous methods. ANS combines the compression ratio of arithmetic coding (which uses a nearly accurate probability distribution), with a processing cost similar to that of Huffman coding. In the tabled ANS (tANS) variant, this is achieved by constructing a finite-state machine to operate on a large alphabet without using multiplication. Among others, ANS is used in the Facebook Zstandard compressor
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Delta Encoding
Delta encoding is a way of storing or transmitting data in the form of '' differences'' (deltas) between sequential data rather than complete files; more generally this is known as data differencing. Delta encoding is sometimes called delta compression, particularly where archival histories of changes are required (e.g., in revision control software). The differences are recorded in discrete files called "deltas" or "diffs". In situations where differences are small – for example, the change of a few words in a large document or the change of a few records in a large table – delta encoding greatly reduces data redundancy. Collections of unique deltas are substantially more space-efficient than their non-encoded equivalents. From a logical point of view the difference between two data values is the information required to obtain one value from the other – see relative entropy. The difference between identical values (under some equivalence) is often called ''0'' or the neut ...
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