Editing Lossy compression (section)

== Information loss ==
Lossy compression formats suffer from [[generation loss]]: repeatedly compressing and decompressing the file will cause it to progressively lose quality. This is in contrast with [[lossless data compression]], where data will not be lost via the use of such a procedure. [[information theory|Information-theoretical]] foundations for lossy data compression are provided by [[rate-distortion theory]].  Much like the use of [[probability]] in optimal [[coding theory]], rate-distortion theory heavily draws on [[Bayesian theory|Bayesian]] [[estimation theory|estimation]] and [[decision theory]] in order to model perceptual distortion and even [[aesthetic]] judgment.

There are two basic lossy compression schemes:

* In ''lossy transform [[codec]]s'', samples of picture or sound are taken, chopped into small segments, transformed into a new [[Basis (linear algebra)|basis space]], and [[Quantization (signal processing)|quantized]]. The resulting quantized values are then [[Entropy encoding|entropy coded]].
* In ''lossy predictive codecs'', previous and/or subsequent 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 [[Quantization (signal processing)|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.