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Vector Quantization
Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors. It was originally used for data compression. It works by dividing a large set of points (vectors) into groups having approximately the same number of points closest to them. Each group is represented by its centroid point, as in k-means and some other clustering algorithms. The density matching property of vector quantization is powerful, especially for identifying the density of large and high-dimensional data. Since data points are represented by the index of their closest centroid, commonly occurring data have low error, and rare data high error. This is why VQ is suitable for lossy data compression. It can also be used for lossy data correction and density estimation. Vector quantization is based on the competitive learning paradigm, so it is closely related to the self-organizing map model ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Vector Quantization
Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors. It was originally used for data compression. It works by dividing a large set of points (vectors) into groups having approximately the same number of points closest to them. Each group is represented by its centroid point, as in k-means and some other clustering algorithms. The density matching property of vector quantization is powerful, especially for identifying the density of large and high-dimensional data. Since data points are represented by the index of their closest centroid, commonly occurring data have low error, and rare data high error. This is why VQ is suitable for lossy data compression. It can also be used for lossy data correction and density estimation. Vector quantization is based on the competitive learning paradigm, so it is closely related to the self-organizing map model ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Quantization (signal Processing)
Quantization, in mathematics and digital signal processing, is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often with a finite number of elements. Rounding and truncation are typical examples of quantization processes. Quantization is involved to some degree in nearly all digital signal processing, as the process of representing a signal in digital form ordinarily involves rounding. Quantization also forms the core of essentially all lossy compression algorithms. The difference between an input value and its quantized value (such as round-off error) is referred to as quantization error. A device or algorithmic function that performs quantization is called a quantizer. An analog-to-digital converter is an example of a quantizer. Example For example, rounding a real number x to the nearest integer value forms a very basic type of quantizer – a ''uniform'' one. A typical (''mid-tread'') uni ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Vector Space
In mathematics and physics, a vector space (also called a linear space) is a set whose elements, often called ''vectors'', may be added together and multiplied ("scaled") by numbers called '' scalars''. Scalars are often real numbers, but can be complex numbers or, more generally, elements of any field. The operations of vector addition and scalar multiplication must satisfy certain requirements, called ''vector axioms''. The terms real vector space and complex vector space are often used to specify the nature of the scalars: real coordinate space or complex coordinate space. Vector spaces generalize Euclidean vectors, which allow modeling of physical quantities, such as forces and velocity, that have not only a magnitude, but also a direction. The concept of vector spaces is fundamental for linear algebra, together with the concept of matrix, which allows computing in vector spaces. This provides a concise and synthetic way for manipulating and studying systems of linear eq ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Internet Engineering Task Force
The Internet Engineering Task Force (IETF) is a standards organization for the Internet and is responsible for the technical standards that make up the Internet protocol suite (TCP/IP). It has no formal membership roster or requirements and all its participants are volunteers. Their work is usually funded by employers or other sponsors. The IETF was initially supported by the federal government of the United States but since 1993 has operated under the auspices of the Internet Society, an international non-profit organization. Organization The IETF is organized into a large number of working groups and birds of a feather informal discussion groups, each dealing with a specific topic. The IETF operates in a bottom-up task creation mode, largely driven by these working groups. Each working group has an appointed chairperson (or sometimes several co-chairs); a charter that describes its focus; and what it is expected to produce, and when. It is open to all who want to particip ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pyramid Vector Quantization
Pyramid vector quantization (PVQ) is a method used in audio and video codecs to quantize and transmit unit vectors, i.e. vectors whose magnitudes are known to the decoder but whose directions are unknown. PVQ may also be used as part of a gain/shape quantization scheme, whereby the magnitude and direction of a vector are quantized separately from each other. PVQ was initially described in 1986 in the paper "A Pyramid Vector Quantizer" by Thomas R. Fischer. One caveat of PVQ is that it operates under the taxicab distance (L1-norm). Conversion to/from the more familiar Euclidean distance (L2-norm) is possible via vector projection, though results in a less uniform distribution of quantization points (the poles of the Euclidean ''n''-sphere become denser than non-poles). No efficient algorithm for the ideal (i.e., uniform) vector quantization of the Euclidean ''n''-sphere is known as of 2010. This non-uniformity can be reduced by applying deformation like coordinate-wise power befo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Daala
Daala is a video coding format under development by the Xiph.Org Foundation under the lead of Timothy B. Terriberry mainly sponsored by the Mozilla Corporation. Like Theora and Opus, Daala is available free of any royalties and its reference implementation is being developed as free and open-source software. The name is taken from the fictional character of Admiral Natasi Daala from the ''Star Wars'' universe. The reference implementation is written in C and published, together with its source code, as free software under the terms of a BSD-like license. Software patents are being filed for techniques used in and developed for Daala. Those patents are freely licensed to everybody to use for any purpose. However, the patent holders reserve the right to use them to counter patent infringement lawsuits filed by others. Since June 20, 2013, the development is accompanied by a series of sporadically published posts on the underlying technology on the website of the Xiph.Org Founda ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cinepak
Cinepak is a lossy video codec developed by Peter Barrett at SuperMac Technologies, and released in 1991 with the Video Spigot, and then in 1992 as part of Apple Computer's QuickTime video suite. One of the first video compression tools to achieve full motion video on CD-ROM, it was designed to encode 320×240 resolution video at 1× (150 kbyte/s) CD-ROM transfer rates. The original name of this codec was Compact Video, which is why its FourCC identifier is CVID. The codec was ported to Microsoft Windows in 1993. It was also used on fourth- and fifth-generation game consoles, such as the Atari Jaguar CD, Sega CD, Sega Saturn, and 3DO. libavcodec includes a Cinepak decoder and an encoder, both licensed under the terms of the LGPL. History It was the primary video codec of early versions of QuickTime and Microsoft Video for Windows, but was later superseded by Sorenson Video, Intel Indeo, and most recently MPEG-4 Part 2 and H.264/MPEG-4 AVC. However, movies compressed with Ci ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MPEG-4
MPEG-4 is a group of international standards for the compression of digital audio and visual data, multimedia systems, and file storage formats. It was originally introduced in late 1998 as a group of audio and video coding formats and related technology agreed upon by the ISO/IEC Moving Picture Experts Group (MPEG) ( ISO/IEC JTC 1/SC29/WG11) under the formal standard ISO/IEC 14496 – ''Coding of audio-visual objects''. Uses of MPEG-4 include compression of audiovisual data for Internet video and CD distribution, voice (telephone, videophone) and broadcast television applications. The MPEG-4 standard was developed by a group led by Touradj Ebrahimi (later the JPEG president) and Fernando Pereira. Background MPEG-4 absorbs many of the features of MPEG-1 and MPEG-2 and other related standards, adding new features such as (extended) VRML support for 3D rendering, object-oriented composite files (including audio, video and VRML objects), support for externally specified Digital ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
TwinVQ
TwinVQ (transform-domain weighted interleave vector quantization) is an audio compression technique developed by Nippon Telegraph and Telephone Corporation (NTT) Human Interface Laboratories (now Cyber Space Laboratories) in 1994. The compression technique has been used in both standardized and proprietary designs. TwinVQ in MPEG-4 In the context of the MPEG-4 Audio (MPEG-4 Part 3), TwinVQ is an audio codec optimized for audio coding at ultra low bitrates around 8 kbit/s. TwinVQ is one of the object types defined in MPEG-4 Audio, published as subpart 4 of ISO/IEC 14496-3 (for the first time in 1999 - a.k.a. MPEG-4 Audio version 1). This object type is based on a general audio transform coding scheme which is integrated with the AAC coding frame work, a spectral flattening module, and a weighted interleave vector quantization module. This scheme reportedly has high coding gain for low bit rate and potential robustness against channel errors and packet loss, since it does not use ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prefix Code
A prefix code is a type of code system distinguished by its possession of the "prefix property", which requires that there is no whole code word in the system that is a prefix (initial segment) of any other code word in the system. It is trivially true for fixed-length code, so only a point of consideration in variable-length code. For example, a code with code words has the prefix property; a code consisting of does not, because "5" is a prefix of "59" and also of "55". A prefix code is a uniquely decodable code: given a complete and accurate sequence, a receiver can identify each word without requiring a special marker between words. However, there are uniquely decodable codes that are not prefix codes; for instance, the reverse of a prefix code is still uniquely decodable (it is a suffix code), but it is not necessarily a prefix code. Prefix codes are also known as prefix-free codes, prefix condition codes and instantaneous codes. Although Huffman coding is just one of many alg ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Entropy Code
In information theory, an entropy coding (or entropy encoding) is any lossless data compression method that attempts to approach the lower bound declared by 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_(d(x))\geq \mathbb E_ \log_b(P(x))/math>, 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 may be useful. These static codes incl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
