|
Entropy Coded
In information theory, an entropy coding (or entropy encoding) is any lossless compression, lossless data compression method that attempts to approach the lower bound declared by Claude Shannon, Shannon's source coding theorem, which states that any lossless data compression method must have expected code length greater or equal to the entropy of the source. More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies \mathbb E_[l(d(x))] \geq \mathbb E_[-\log_b(P(x))], where l is the number of symbols in a code word, d is the coding function, b is the number of symbols used to make output codes and P is the probability of the source symbol. An entropy coding attempts to approach this lower bound. Two of the most common entropy coding techniques are Huffman coding and arithmetic coding. If the approximate entropy characteristics of a data stream are known in advance (especially for signal compression), a simpler static code m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Information Theory
Information theory is the scientific study of the quantification (science), quantification, computer data storage, storage, and telecommunication, communication of information. The field was originally established by the works of Harry Nyquist and Ralph Hartley, in the 1920s, and Claude Shannon in the 1940s. The field is at the intersection of probability theory, statistics, computer science, statistical mechanics, information engineering (field), information engineering, and electrical engineering. A key measure in information theory is information entropy, entropy. Entropy quantifies the amount of uncertainty involved in the value of a random variable or the outcome of a random process. For example, identifying the outcome of a fair coin flip (with two equally likely outcomes) provides less information (lower entropy) than specifying the outcome from a roll of a dice, die (with six equally likely outcomes). Some other important measures in information theory are mutual informat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Thomas Wiegand
Thomas Wiegand (born 6 May 1970 in Wismar) is a German electrical engineer who substantially contributed to the creation of the H.264/AVC, H.265/HEVC, and H.266/VVC video coding standards. For H.264/AVC, Wiegand was one of the chairmen of the Joint Video Team (JVT) standardization committee that created the standard and was the chief editor of the standard itself. He was also a very active technical contributor to the H.264/AVC, H.265/HEVC, and H.266/VVC video coding standards. Wiegand also holds a chairmanship position in the ITU-T VCEG of ITU-T Study Group 16 and previously in ISO/IEC MPEG standardization organizations. In July 2006, the video coding work of the ITU-T jointly led by Gary J. Sullivan and Wiegand for the preceding six years was voted as the most influential area of the standardization work of the CCITT and ITU-T in their 50-year history. Since 2018, Wiegand has served as chair of the ITU/WHO Focus Group on Artificial Intelligence for Health (FG-AI4H). Sinc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
David MacKay (scientist)
Professor Sir David John Cameron MacKay (22 April 1967 – 14 April 2016) was a British physicist, mathematician, and academic. He was the Regius Professor of Engineering in the Department of Engineering at the University of Cambridge and from 2009 to 2014 was Chief Scientific Advisor to the UK Department of Energy and Climate Change (DECC). MacKay wrote the book ''Sustainable Energy – Without the Hot Air''. Education MacKay was educated at Newcastle High School and represented Britain in the International Physics Olympiad in Yugoslavia in 1985, receiving the first prize for experimental work. He continued his education at Trinity College, Cambridge, and received a Bachelor of Arts degree in Natural Sciences (Experimental and theoretical physics) in 1988. He went to the California Institute of Technology (Caltech) as a Fulbright Scholar, where his supervisor was John Hopfield. He was awarded a PhD in 1992. Career and research In January 1992 MacKay was appointed the Roya ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Range Coding
Range coding (or range encoding) is an entropy coding method defined by G. Nigel N. Martin in a 1979 paper,, 100000)) using the probability distribution . The encoder breaks down the range [0, 100000) into three subranges: A: [ 0, 60000) B: [ 60000, 80000) : [ 80000, 100000) Since our first symbol is an A, it reduces our initial range down to [0, 60000). The second symbol choice leaves us with three sub-ranges of this range. We show them following the already-encoded 'A': AA: [ 0, 36000) AB: [ 36000, 48000) A: [ 48000, 60000) With two symbols encoded, our range is now [0, 36000) and our third symbol leads to the following choices: AAA: [ 0, 21600) AAB: [ 21600, 28800) AA: [ 28800, 36000) This time it is the second of our three choices that represent the message we want to encode, and our range becomes [21600, 28800). It may look harder to determine our sub-ranges in this case, but it is actually not: we can mere ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Context-adaptive Binary Arithmetic Coding
Context-adaptive binary arithmetic coding (CABAC) is a form of entropy encoding used in the H.264/MPEG-4 AVC and High Efficiency Video Coding (HEVC) standards. It is a lossless compression technique, although the video coding standards in which it is used are typically for lossy compression applications. CABAC is notable for providing much better compression than most other entropy encoding algorithms used in video encoding, and it is one of the key elements that provides the H.264/AVC encoding scheme with better compression capability than its predecessors. In H.264/MPEG-4 AVC, CABAC is only supported in the Main and higher profiles (but not the extended profile) of the standard, as it requires a larger amount of processing to decode than the simpler scheme known as context-adaptive variable-length coding (CAVLC) that is used in the standard's Baseline profile. CABAC is also difficult to parallelize and vectorize, so other forms of parallelism (such as spatial region parallelis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
