Quantization (signal processing): Difference between revisions

Revision as of 18:35, 5 May 2005

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==Quantization and Data Compression==

Quantization plays a major part in [[lossy data compression]].
In some Indeedcases, quantization can be viewed as the fundamental element that distinguishes [[lossy data compression]] from [[lossless data compression]], and the use of quantization is nearly always motivated by the need to reduce the amount of data needed to represent a signal.

In some compression schemes, like [[MP3]] or [[Vorbis]], compression is also achieved by selectively discarding information and so quantization is not always the fundamental difference between lossy and lossless.

One example of such lossy a compression scheme is [[JPEG]] compression.

During JPEG encoding, the data representing an image (typically 8-bits for each of three color components per pixel ___location) is processed using a [[discrete cosine transform]] and is then quantized and [[entropy encoding|entropy coded]].

By reducing the precision of the transformed values using quantization, the number of bits needed to represent the image can be reduced substantially.
For example, images can often be represented with acceptable quality using JPEG at less than 3 bits per pixel (as opposed the the typical 24 bits per pixel needed prior to JPEG compression). Indeed, even
Even the original representation using 24 bits per pixel requires quantization for its [[pulse-code modulation|PCM]] sampling structure.

Compression of other types of data (e.g., audio or video signals) follows very similar principles. For example, [[MP3]] audio coding also involves transformation followed by quantization followed by entropy coding. For video, one additional technique (called [[motion compensation]]) is typically employed in addition to the other elements.

In modern compression technology, the [[information entropy|entropy]] of the output of a quantizer matters more than the number of possible values of its output (the number of values being <math>2^M</math> in the above example).