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

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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 coded 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.

Video codecs based on vector quantization

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• Cinepak
• Sorenson codec

Audio codecs based on vector quantization

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• TwinVQ

See also

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• speech coding
• Ogg Vorbis
• Voronoi diagram
• rate-distortion function
• data clustering
• Learning Vector Quantization

Part of this article was originally based on material from the Free On-line Dictionary of Computing and is used with Foldoc license under the GFDL.

External links

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• http://www.data-compression.com/vq.html
• List of papers and resources about quantization

Lossy compression algorithms

Quantification vectorielle