Vector quantization: Difference between revisions

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{{technical}}

In [[data compression]], '''vector quantization''' is a [[quantization]] technique often used in [[lossy data compression]] in which the basic idea is to code or replace with a key, values from a multidimensional [[vector space]] into values from a discrete [[subspace]] of lower dimension. The lower-space vector requires less storage space and the data is thus compressed. The transformation into the subspace is usually achieved through [[projection]], or by using a [[codebook]]. In some cases, a codebook implementation can be also used to [[entropy code]] the discrete value in the same step by generating a [[prefix code]]d variable-length encoded value as its output.

In [[data compression]], '''vector quantization''' is a [[quantization]] technique often used in [[lossy data compression]] in which the basic idea is to code or replace with a key, values from a multidimensional [[vector space]] into values from a discrete [[subspace]] of lower dimension.

== Explanation ==

In [[data compression]], '''vector quantization''' is a [[quantization]] technique often used in [[lossy data compression]] in which the basic idea is to code or replace with a key, values from a multidimensional [[vector space]] into values from a discrete [[subspace]] of lower dimension. The lower-space vector requires less storage space and the data is thus compressed. The transformation into the subspace is usually achieved through [[projection]], or by using a [[codebook]]. In some cases, a codebook implementation can be also used to [[entropy code]] the discrete value in the same step by generating a [[prefix code]]d variable-length encoded value as its output.

[[Twin vector quantization]] (VQF) is part of the [[MPEG-4]] standard dealing with time ___domain weighted interleaved vector quantization.