iPedia Free Information Center

Information about Average Bitrate

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. It can have higher bitrate and lower bitrate parts, and the average bitrate for a certain timeframe is obtained by dividing the number of bits used during the timeframe by the number of seconds in the timeframe. Bitrate is not reliable as a standalone measure of audio/video quality since more efficient compression methods need less bitrate to encode material at a similar quality.

Average bit rate can also refer to a form of variable bitrate encoding where the encoder will try to reach a target average bitrate or file size while allowing the bitrate to vary between different parts of the audio or video. As it is a form of variable bitrate, this allows more complex portions of the material to use more bits and less complex areas to use fewer bits. However, bitrate will not vary as much as variable bitrate encoding. Two-pass encoding is usually needed for accurate ABR encoding, as on the first pass the encoder has no way of knowing what parts of the audio or video need the most bitrate to be encoded.

See also

Data compression methods
 •  • [ e]
Lossless compression methods
Theory
Entropy Complexity Redundancy		Entropy encoding
Huffman Adaptive Huffman Arithmetic (Shannon-Fano Range) Golomb Exp-Golomb Universal (Elias Fibonacci)		Dictionary
LZ77/78 LZW LZO DEFLATE LZMA LZX		Others
RLE BWT PPM DMC
Audio compression methods
Theory
Convolution Sampling Nyquist–Shannon theorem		Audio codecs parts
LPC (LAR LSP) WLPC CELP ACELP A-law μ-law MDCT Fourier transform Psychoacoustic model		Others
Dynamic range compression Speech compression Sub-band coding
Image compression methods
Terms
Color space Pixel Chroma subsampling Compression artifact		Methods
RLE Fractal Wavelet SPIHT DCT KLT		Others
Bit rate Test images PSNR quality measure Quantization
Video compression
Terms
Video Characteristics Frame Frame types Video quality		Video codec parts
Motion compensation DCT Quantization		Others
Video codecs Rate distortion theory (CBR ABR VBR)
Timeline of information theory, data compression, and error-correcting codes
(See for formats and for codecs)
MPEG-1 Audio Layer 3

File extension: .mp3
MIME type: audio/mpeg
Type of format: Audio MPEG-1 Audio Layer 3, more commonly referred to as MP3, is an audio encoding format.
..... Click the link for more information.
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.
..... Click the link for more information.
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.
..... Click the link for more information.
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.
..... Click the link for more information.
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.
..... Click the link for more information.
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.
..... Click the link for more information.
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
..... Click the link for more information.
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.
..... Click the link for more information.
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
..... Click the link for more information.
In computer science, the Kolmogorov complexity (also known as descriptive complexity, Kolmogorov-Chaitin complexity, stochastic complexity, algorithmic entropy, or program-size complexity
..... Click the link for more information.
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.
..... Click the link for more information.
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
..... Click the link for more information.
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
..... Click the link for more information.
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
..... Click the link for more information.
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.
..... Click the link for more information.
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.
..... Click the link for more information.
The introduction to this article provides insufficient context for those unfamiliar with the subject matter.
Please help [ improve the introduction] to meet Wikipedia's layout standards.

..... Click the link for more information.
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:

..... Click the link for more information.
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.
..... Click the link for more information.
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:
  1. Write it in binary.

..... Click the link for more information.
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.
..... Click the link for more information.
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')
..... Click the link for more information.
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] .
..... Click the link for more information.
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.
..... Click the link for more information.
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.
..... Click the link for more information.
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.
..... Click the link for more information.
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.
..... Click the link for more information.
LZX is the name of an LZ77 family compression algorithm. It is also the name of a file archiver with the same name. Both were invented by Jonathan Forbes and Tomi Poutanen.
..... Click the link for more information.
Run-length encoding (RLE) is a very simple form of data compression in which runs of data (that is, sequences in which the same data value occurs in many consecutive data elements) are stored as a single data value and count, rather than as the original run.
..... Click the link for more information.
The Burrows-Wheeler transform (BWT, also called block-sorting compression), is an algorithm used in data compression techniques such as bzip2. It was invented by Michael Burrows and David Wheeler in 1994 while working at Digital Systems Research Center in Palo Alto,
..... Click the link for more information.


This article is copied from an article on Wikipedia.org - the free encyclopedia created and edited by online user community. The text was not checked or edited by anyone on our staff. Although the vast majority of the wikipedia encyclopedia articles provide accurate and timely information please do not assume the accuracy of any particular article. This article is distributed under the terms of GNU Free Documentation License.
Herod_Archelaus


page counter