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In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. 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. 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.
In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. The different versions of the photo of the cat on this page show how higher degrees of approximation create coarser images as more details are removed. This is opposed to lossless data compression which does not degrade the data. The amount of data reduction possible using lossy compression is much higher than using lossless techniques.
Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved compression rates.
PNG, or Portable Network Graphics, is a popular image format that is widely used on the internet. It was developed in the mid-1990s as a replacement for the GIF format, which had several limitations, such as limited color depth and the use of patented compression algorithms. PNG offers several advantages over GIF, such as support for alpha transparency and a larger color palette.
Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
In information theory, an entropy coding 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.
A discrete cosine transform (DCT) expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies. The DCT, first proposed by Nasir Ahmed in 1972, is a widely used transformation technique in signal processing and data compression. It is used in most digital media, including digital images, digital video, digital audio, digital television, digital radio, and speech coding. DCTs are also important to numerous other applications in science and engineering, such as digital signal processing, telecommunication devices, reducing network bandwidth usage, and spectral methods for the numerical solution of partial differential equations.
LZ77 and LZ78 are 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. These two algorithms form the basis for many variations including LZW, LZSS, LZMA and others. Besides their academic influence, these algorithms formed the basis of several ubiquitous compression schemes, including GIF and the DEFLATE algorithm used in PNG and ZIP.
OpenEXR is a high-dynamic range, multi-channel raster file format, released as an open standard along with a set of software tools created by Industrial Light & Magic (ILM), under a free software license similar to the BSD license.
In telecommunications and computing, bit rate is the number of bits that are conveyed or processed per unit of time.
Prediction by partial matching (PPM) is an adaptive statistical data compression technique based on context modeling and prediction. PPM models use a set of previous symbols in the uncompressed symbol stream to predict the next symbol in the stream. PPM algorithms can also be used to cluster data into predicted groupings in cluster analysis.
ART is a proprietary image file format used mostly by the America Online (AOL) service and client software.
The move-to-front (MTF) transform is an encoding of data designed to improve the performance of entropy encoding techniques of compression. When efficiently implemented, it is fast enough that its benefits usually justify including it as an extra step in data compression algorithm.
WavPack is a free and open-source lossless audio compression format and application implementing the format. It is unique in the way that it supports hybrid audio compression alongside normal compression which is similar to how FLAC works. It also supports compressing a wide variety of lossless formats, including various variants of PCM and also DSD as used in SACDs, together with its support for surround audio.
G.722 is an ITU-T standard 7 kHz wideband audio codec operating at 48, 56 and 64 kbit/s. It was approved by ITU-T in November 1988. Technology of the codec is based on sub-band ADPCM (SB-ADPCM). The corresponding narrow-band codec based on the same technology is G.726.
An image file format is a file format for a digital image. There are many formats that can be used, such as JPEG, PNG, and GIF. Most formats up until 2022 were for storing 2D images, not 3D ones. The data stored in an image file format may be compressed or uncompressed. If the data is compressed, it may be done so using lossy compression or lossless compression. For graphic design applications, vector formats are often used. Some image file formats support transparency.
Lempel–Ziv–Stac is a lossless data compression algorithm that uses a combination of the LZ77 sliding-window compression algorithm and fixed Huffman coding. It was originally developed by Stac Electronics for tape compression, and subsequently adapted for hard disk compression and sold as the Stacker disk compression software. It was later specified as a compression algorithm for various network protocols. LZS is specified in the Cisco IOS stack.
An audio coding format is a content representation format for storage or transmission of digital audio. Examples of audio coding formats include MP3, AAC, Vorbis, FLAC, and Opus. A specific software or hardware implementation capable of audio compression and decompression to/from a specific audio coding format is called an audio codec; an example of an audio codec is LAME, which is one of several different codecs which implements encoding and decoding audio in the MP3 audio coding format in software.
Zstandard, commonly known by the name of its reference implementation zstd, is a lossless data compression algorithm developed by Yann Collet at Facebook. Zstd is the reference implementation in C. Version 1 of this implementation was released as open-source software on 31 August 2016.
References
- ↑ "Adaptive compression". PC Magazine Encyclopedia. Retrieved 21 April 2011.[ dead link ]
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