Information about Constant Bit Rate
Constant bitrate (CBR) is a term used in telecommunications, relating to the quality of service. Compare with variable bit rate.
When referring to codecs, constant bit rate encoding means that the rate at which a codec's output data should be consumed is constant. CBR is useful for streaming multimedia content on limited capacity channels since it is the maximum bit rate that matters, not the average, so CBR would be used to take advantage of all of the capacity. CBR would not be the optimal choice for storage as it would not allocate enough data for complex sections (resulting in degraded quality) while wasting data on simple sections.
The problem of not allocating enough data for complex sections could be solved by choosing a high bitrate (eg, 256 kbit/s or 320 kbit/s) to ensure that there will be enough bits for the entire encoding process, though the size of the file at the end would be proportionally larger.
Most coding schemes such as Huffman coding or run-length encoding produce variable-length codes, making perfect CBR difficult to achieve. This is partly solved by varying the quantization (quality), and fully solved by the use of padding. (However, CBR is implied in a simple scheme like reducing all 16-bit audio samples to 8-bits.)
(See for formats and for codecs)
A codec is a device or program capable of performing encoding and decoding on a digital data stream or signal. The word codec may be a combination of any of the following: 'Compressor-Dec
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When referring to codecs, constant bit rate encoding means that the rate at which a codec's output data should be consumed is constant. CBR is useful for streaming multimedia content on limited capacity channels since it is the maximum bit rate that matters, not the average, so CBR would be used to take advantage of all of the capacity. CBR would not be the optimal choice for storage as it would not allocate enough data for complex sections (resulting in degraded quality) while wasting data on simple sections.
The problem of not allocating enough data for complex sections could be solved by choosing a high bitrate (eg, 256 kbit/s or 320 kbit/s) to ensure that there will be enough bits for the entire encoding process, though the size of the file at the end would be proportionally larger.
Most coding schemes such as Huffman coding or run-length encoding produce variable-length codes, making perfect CBR difficult to achieve. This is partly solved by varying the quantization (quality), and fully solved by the use of padding. (However, CBR is implied in a simple scheme like reducing all 16-bit audio samples to 8-bits.)
See also
| Lossless compression methods | ||||
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| Audio compression methods |
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| Image compression methods |
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| Timeline of information theory, data compression, and error-correcting codes | ||||
Telecommunication is the transmission of signals over a distance for the purpose of communication. In modern times, this process typically involves the sending of electromagnetic waves by electronic transmitters, but in earlier times telecommunication may have involved the use of
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Quality of Service, abbreviated QoS, refers to resource reservation control mechanisms. Quality of Service can provide different priority to different users or data flows, or guarantee a certain level of performance to a data flow in accordance with requests from the
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Variable bitrate (VBR), or less commonly variable bit rate, is a term used in telecommunications and computing that relates to the bitrate used in sound or video encoding. As opposed to constant bitrate (CBR), VBR files vary the amount of output data per time segment.
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- codec, see Codec (disambiguation).
A codec is a device or program capable of performing encoding and decoding on a digital data stream or signal. The word codec may be a combination of any of the following: 'Compressor-Dec
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Huffman coding is an entropy encoding algorithm used for lossless data compression. The term refers to the use of a variable-length code table for encoding a source symbol (such as a character in a file) where the variable-length code table has been derived in a particular way
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bitrate (sometimes written bit rate, data rate or as a variable R or fb) is the number of bits that are conveyed or processed per unit of time. Bit rate is synonymous to data rate and digital bandwidth.
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Average bitrate refers to the average amount of data transferred per second. This is commonly referred to for digital music or video. An MP3 file, for example, that has an average bit rate of 128 kbit/s transfers, on average, 128,000 bits every second.
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Variable bitrate (VBR), or less commonly variable bit rate, is a term used in telecommunications and computing that relates to the bitrate used in sound or video encoding. As opposed to constant bitrate (CBR), VBR files vary the amount of output data per time segment.
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data compression or source coding is the process of encoding information using fewer bits (or other information-bearing units) than an un-encoded representation would use through use of specific encoding schemes.
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Lossless data compression is a class of data compression algorithms that allows the exact original data to be reconstructed from the compressed data. This can be contrasted to lossy data compression, which does not allow the exact original data to be reconstructed from the
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Information theory is a branch of applied mathematics and engineering involving the quantification of information to find fundamental limits on compressing and reliably communicating data.
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Shannon entropy or information entropy is a measure of the uncertainty associated with a random variable.
Shannon entropy quantifies the information contained in a piece of data: it is the minimum average message length, in bits (if using base-2 logarithms), that must
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Shannon entropy quantifies the information contained in a piece of data: it is the minimum average message length, in bits (if using base-2 logarithms), that must
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In computer science, the Kolmogorov complexity (also known as descriptive complexity, Kolmogorov-Chaitin complexity, stochastic complexity, algorithmic entropy, or program-size complexity
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Redundancy in information theory is the number of bits used to transmit a message minus the number of bits of actual information in the message. Informally, it is the amount of wasted "space" used to transmit certain data.
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In information theory an entropy encoding is a lossless data compression scheme that is independent of the media’s specific characteristics.
One of the main types of entropy coding assigns codes to symbols so as to match code lengths with the probabilities of the
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One of the main types of entropy coding assigns codes to symbols so as to match code lengths with the probabilities of the
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Huffman coding is an entropy encoding algorithm used for lossless data compression. The term refers to the use of a variable-length code table for encoding a source symbol (such as a character in a file) where the variable-length code table has been derived in a particular way
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Adaptive Huffman coding (also called Dynamic Huffman coding) is an adaptive coding technique based on Huffman coding, building the code as the symbols are being transmitted, having no initial knowledge of source distribution, that allows one-pass encoding and adaptation to
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Arithmetic coding is a method for lossless data compression. Normally, a string of characters such as the words "hello there" is represented using a fixed number of bits per character, as in the ASCII code.
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Range encoding is a form of arithmetic coding, a data compression method, that is believed to be free from arithmetic coding related patents. It is on this basis that interest in range encoding has arisen, particularly in the open source community.
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An Exponential-Golomb code (or just Exp-Golomb code) of order is a type of universal code, parameterized by a whole number . To encode a nonnegative integer in an order- exp-Golomb code, one can use the following method:
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universal code for integers is a prefix code that maps the positive integers onto binary codewords, with the additional property that whatever the true probability distribution on integers, as long as the distribution is monotonic (i.e.
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Elias gamma code is a universal code encoding positive integers. It is used most commonly when coding integers whose upper-bound cannot be determined beforehand.
To code a number:
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To code a number:
- Write it in binary.
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Fibonacci coding is a universal code which encodes positive integers into binary code words. All tokens end with "11" and have no "11" before the end.
The formula used to generate Fibonacci codes is:
where F(i) is the i-th Fibonacci number.
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The formula used to generate Fibonacci codes is:
where F(i) is the i-th Fibonacci number.
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A dictionary coder, also sometimes known as a substitution coder, is any of a number 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')
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LZ77 and LZ78 are the names for 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 [1] .
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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.
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Lempel-Ziv-Oberhumer (LZO) is a data compression algorithm that is focused on decompression speed. The algorithm is lossless and the reference implementation is thread safe.
A free software tool which implements it is lzop.
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A free software tool which implements it is lzop.
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DEFLATE is a lossless data compression algorithm that uses a combination of the LZ77 algorithm and Huffman coding. It was originally defined by Phil Katz for version 2 of his PKZIP archiving tool, and was later specified in RFC 1951.
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The Lempel-Ziv-Markov chain-Algorithm (LZMA) is an algorithm for data compression in development since 1998[1] and used in the 7z format of the 7-Zip archiver.
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