"Source coding" redirects here. For the term in computer programming, see Source code.
In information theory, data compression, source coding,[1] or bit-rate reduction is the process of encoding information using fewer bits than the original representation.[2] 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.[3] 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 is done at the source of the data before it is stored or transmitted.[4] 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.
Compression is useful because it reduces the resources required to store and transmit data. Computational resources are consumed in the compression and decompression processes. Data compression is subject to a space-time complexity trade-off. For instance, a compression scheme for video may require expensive hardware for the video to be decompressed fast enough to be viewed as it is being decompressed, and the option to decompress the video in full before watching it may be inconvenient or require additional storage. The design of data compression schemes involves trade-offs among various factors, including the degree of compression, the amount of distortion introduced (when using lossy data compression), and the computational resources required to compress and decompress the data.[5]
^Cite error: The named reference Wade was invoked but never defined (see the help page).
^Cite error: The named reference mahdi53 was invoked but never defined (see the help page).
^Cite error: The named reference PujarKadlaskar was invoked but never defined (see the help page).
^Cite error: The named reference Salomon was invoked but never defined (see the help page).
^Cite error: The named reference Tank was invoked but never defined (see the help page).
In information theory, datacompression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original...
Lossless compression is a class of datacompression that allows the original data to be perfectly reconstructed from the compressed data with no loss...
Datacompression ratio, also known as compression power, is a measurement of the relative reduction in size of data representation produced by a data...
technology, lossy compression or irreversible compression is the class of datacompression methods that uses inexact approximations and partial data discarding...
Image compression is a type of datacompression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage...
caused by the application of lossy compression. Lossy datacompression involves discarding some of the media's data so that it becomes small enough to...
asymmetry, in the context of datacompression, refer to the time relation between compression and decompression for a given compression algorithm. If an algorithm...
year. The compression is performed in real time, as the signals are acquired; it calculates a compression decision before all the compressed data is received...
engine Compression (geology) Compression or compressive strength Datacompression, reducing the data required for information Audio compression (data), reducing...
Deflate (stylized as DEFLATE, and also called Flate) is a lossless datacompression file format that uses a combination of LZ77 and Huffman coding. It...
HTTP compression is a capability that can be built into web servers and web clients to improve transfer speed and bandwidth utilization. HTTP data is compressed...
Smart DataCompression is a compressed GIS dataset format developed by ESRI. It stores all types of feature data and attribute information together as...
image compression algorithms (e.g. JPEG), S3TC's fixed-rate datacompression coupled with the single memory access (cf. Color Cell Compression and some...
method of lossy compression for digital images, particularly for those images produced by digital photography. The degree of compression can be adjusted...
genomic re-sequencing data emphasizes the growing demand for efficient methods for genomic datacompression. While standard datacompression tools (e.g., zip...
compression a video frame is compressed using different algorithms with different advantages and disadvantages, centered mainly around amount of data...
IANA. Compression-only formats should often be denoted by the media type of the decompressed data, with a content coding indicating the compression format...
LZ77 and LZ78 are the two lossless datacompression algorithms published in papers by Abraham Lempel and Jacob Ziv in 1977 and 1978. They are also known...
control Layer 6, the presentation layer: Source coding (digitization and datacompression), and information theory. Cryptography (may occur at any layer) It...
and compression. A system that predicts the posterior probabilities of a sequence given its entire history can be used for optimal datacompression (by...
particular type of optimal prefix code that is commonly used for lossless datacompression. The process of finding or using such a code is Huffman coding, an...
targeted at mobile phones. It is known for its small app size and datacompression technology, making it popular in emerging markets where people tend...
runtime. Texture data is often the largest source of memory usage in a mobile application. In their seminal paper on texture compression, Beers, Agrawala...
Global Information