Quantization (signal processing): Difference between revisions

Revision as of 20:26, 5 May 2005

Revision as of 18:22, 6 May 2005

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==Quantization and Data Compression==

Quantization plays a major part in [[lossy data compression]].

In somemany cases, 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 informationsome anddata, soan action that can be analyzed as a quantization isprocess not(e.g., alwaysa thevector fundamentalquantization differenceprocess) betweenor lossycan andbe considered a different kind of lossy losslessprocess.

One example of sucha lossy a compression scheme that uses quantization is [[JPEG]] image compression.

During JPEG encoding, the data representing an image (typically 8-bits for each of three color components per pixel) 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.