Internet Compression Program

Compression is one of the most important effects available to audio engineers. It is not uncommon for songs you hear on the radio to go through 4 or 5 different compressors before you hear them: one while recording, one or two. Earn when you search, browse, and shop. Internet Explorer Values. Diversity and inclusion Accessibility Environment.

Data compression - Wikipedia, the free encyclopedia. For the term in computer programming, see Source code. In signal processing, data compression, source coding. 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. In the context of data transmission, it is called source coding (encoding done at the source of the data before it is stored or transmitted) in opposition to channel coding.

Computational resources are consumed in the compression process and, usually, in the reversal of the process (decompression). Data compression is subject to a space. 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. Lossless compression is possible because most real- world data exhibits statistical redundancy. For example, an image may have areas of color that do not change over several pixels; instead of coding .

This is a basic example of run- length encoding; there are many schemes to reduce file size by eliminating redundancy. The Lempel. DEFLATE is used in PKZIP, Gzip, and PNG. Also noteworthy is the LZR (Lempel- Ziv. For most LZ methods, this table is generated dynamically from earlier data in the input. The table itself is often Huffman encoded (e.

Current LZ- based coding schemes that perform well are Brotli and LZX. LZX is used in Microsoft's CAB format. The best modern lossless compressors use probabilistic models, such as prediction by partial matching. The basic task of grammar- based codes is constructing a context- free grammar deriving a single string. Sequitur and Re- Pair are practical grammar compression algorithms for which software is publicly available. In a further refinement of the direct use of probabilistic modelling, statistical estimates can be coupled to an algorithm called arithmetic coding.

Arithmetic coding is a more modern coding technique that uses the mathematical calculations of a finite- state machine to produce a string of encoded bits from a series of input data symbols. It can achieve superior compression to other techniques such as the better- known Huffman algorithm. It uses an internal memory state to avoid the need to perform a one- to- one mapping of individual input symbols to distinct representations that use an integer number of bits, and it clears out the internal memory only after encoding the entire string of data symbols. Arithmetic coding applies especially well to adaptive data compression tasks where the statistics vary and are context- dependent, as it can be easily coupled with an adaptive model of the probability distribution of the input data.

An early example of the use of arithmetic coding was its use as an optional (but not widely used) feature of the JPEG image coding standard. It has since been applied in various other designs including H.

MPEG- 4 AVC and HEVC for video coding. Lossy data compression is the converse of lossless data compression. In these schemes, some loss of information is acceptable. Dropping nonessential detail from the data source can save storage space. Lossy data compression schemes are designed by research on how people perceive the data in question. For example, the human eye is more sensitive to subtle variations in luminance than it is to the variations in color. JPEGimage compression works in part by rounding off nonessential bits of information.

A number of popular compression formats exploit these perceptual differences, including those used in music files, images, and video. Lossy image compression can be used in digital cameras, to increase storage capacities with minimal degradation of picture quality. Similarly, DVDs use the lossy MPEG- 2video coding format for video compression. In lossy audio compression, methods of psychoacoustics are used to remove non- audible (or less audible) components of the audio signal. Compression of human speech is often performed with even more specialized techniques; speech coding, or voice coding, is sometimes distinguished as a separate discipline from audio compression.

Different audio and speech compression standards are listed under audio coding formats. Voice compression is used in internet telephony, for example, audio compression is used for CD ripping and is decoded by the audio players. These areas of study were essentially forged by Claude Shannon, who published fundamental papers on the topic in the late 1. Coding theory is also related to this. The idea of data compression is also deeply connected with statistical inference. This equivalence has been used as a justification for using data compression as a benchmark for . Thus, one can consider data compression as data differencing with empty source data, the compressed file corresponding to a .

Audio compression algorithms are implemented in software as audio codecs. Lossy audio compression algorithms provide higher compression at the cost of fidelity and are used in numerous audio applications. These algorithms almost all rely on psychoacoustics to eliminate less audible or meaningful sounds, thereby reducing the space required to store or transmit them.

For example, one 6. MB compact disc (CD) holds approximately one hour of uncompressed high fidelity music, less than 2 hours of music compressed losslessly, or 7 hours of music compressed in the MP3 format at a medium bit rate. A digital sound recorder can typically store around 2. MB. Compression ratios are around 5. Lossless compression is unable to attain high compression ratios due to the complexity of waveforms and the rapid changes in sound forms. Codecs like FLAC, Shorten, and TTA use linear prediction to estimate the spectrum of the signal.

Many of these algorithms use convolution with the filter . The process is reversed upon decompression. When audio files are to be processed, either by further compression or for editing, it is desirable to work from an unchanged original (uncompressed or losslessly compressed). Processing of a lossily compressed file for some purpose usually produces a final result inferior to the creation of the same compressed file from an uncompressed original. In addition to sound editing or mixing, lossless audio compression is often used for archival storage, or as master copies.

A number of lossless audio compression formats exist. Shorten was an early lossless format. Newer ones include Free Lossless Audio Codec (FLAC), Apple's Apple Lossless (ALAC), MPEG- 4 ALS, Microsoft's Windows Media Audio 9 Lossless (WMA Lossless), Monkey's Audio, TTA, and Wav.

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Pack. See list of lossless codecs for a complete listing. Some audio formats feature a combination of a lossy format and a lossless correction; this allows stripping the correction to easily obtain a lossy file. Such formats include MPEG- 4 SLS (Scalable to Lossless), Wav. Pack, and Optim. FROG Dual. Stream. Other formats are associated with a distinct system, such as: Lossy audio compression.

That the lossy spectrograms are different from the uncompressed one indicates that they are, in fact, lossy, but nothing can be assumed about the effect of the changes on perceived quality. Lossy audio compression is used in a wide range of applications.

In addition to the direct applications (MP3 players or computers), digitally compressed audio streams are used in most video DVDs, digital television, streaming media on the internet, satellite and cable radio, and increasingly in terrestrial radio broadcasts. Lossy compression typically achieves far greater compression than lossless compression (data of 5 percent to 2. Most lossy compression reduces perceptual redundancy by first identifying perceptually irrelevant sounds, that is, sounds that are very hard to hear.

Typical examples include high frequencies or sounds that occur at the same time as louder sounds. Those sounds are coded with decreased accuracy or not at all. Due to the nature of lossy algorithms, audio quality suffers when a file is decompressed and recompressed (digital generation loss). This makes lossy compression unsuitable for storing the intermediate results in professional audio engineering applications, such as sound editing and multitrack recording.

However, they are very popular with end users (particularly MP3) as a megabyte can store about a minute's worth of music at adequate quality. Coding methods. Once transformed, typically into the frequency domain, component frequencies can be allocated bits according to how audible they are. Audibility of spectral components calculated using the absolute threshold of hearing and the principles of simultaneous masking. Equal- loudness contours may also be used to weight the perceptual importance of components. Models of the human ear- brain combination incorporating such effects are often called psychoacoustic models. These coders use a model of the sound's generator (such as the human vocal tract with LPC) to whiten the audio signal (i. LPC may be thought of as a basic perceptual coding technique: reconstruction of an audio signal using a linear predictor shapes the coder's quantization noise into the spectrum of the target signal, partially masking it.

In such applications, the data must be decompressed as the data flows, rather than after the entire data stream has been transmitted. Not all audio codecs can be used for streaming applications, and for such applications a codec designed to stream data effectively will usually be chosen.