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Lossy data compression

A lossy data compression method is one where compressing a file and then decompressing it retrieves a file that may well be different to the original, but is "close enough" to be useful in some way. Used a lot on the Internet and especially in streaming media and telephony applications. These methods are typically referred to as codecs in this context.

There are two basic lossy compression schemes:

  • In lossy transform codecs, samples of picture or sound are taken, chopped into small segments, transformed into a new basis space, and quantized. The resulting quantized values are then entropy coded.

  • In lossy predictive codecs, previous decoded data is used to predict the current sound sample or image frame. The error between the predicted data and the real data, together with any extra information needed to reproduce the prediction, is then quantized and coded.

In some systems the two techniques are combined, with transform codecs being used to compress the error signals generated by the predictive stage.

The advantage of lossy methods over lossless methods is that in some cases a lossy method can produce a much smaller compressed file than any known lossless method, while still meeting the requirements of the application.

Lossy methods are most often used for compressing sound or images. In these cases, the retrieved file can be quite different to the original at the bit level while being indistinguishable to the human ear or eye for most practical purposes. Many methods focus on the idiosyncrasies of the human anatomy, taking into account, for example, that the human eye can see only certain frequencies of light. The psychoacoustic model describes how sound can be highly compressed without degrading the quality of the sound. Flaws caused by lossy compression that are noticeable to the human eye or ear are known as compression artifacts.

Lossy methods for still image compression:

Lossy methods for moving image compression:

Lossy methods for sound compression. including music compression:

Lossy methods specifically for speech sound compression:

Lossy methods for geometry data:

Lossy methods for other types of data:

See also: Codec



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