Vector quantization: Difference between revisions

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</ref>

* [[Cinepak]]

* [[Daala]] is transform-based but uses [[pyramid vector quantization]] on transformed coefficients<ref>{{cite IETF |title= Pyramid Vector Quantization for Video Coding | first1= JM. |last1= Valin | draft=draft-valin-videocodec-pvq-00 | date=October 2012 |publisher=[[Internet Engineering Task Force|IETF]] |access-date=2013-12-17 |url=httphttps://tools.ietf.org/html/draft-valin-videocodec-pvq-00}} See also arXiv:1602.05209</ref>

* [[Digital Video Interactive]]: Production-Level Video and Real-Time Video

* [[Indeo]]

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| publisher = Xiph.org

| date = 2007-03-09

| url = httphttps://xiph.org/vorbis/doc/Vorbis_I_spec.html

| access-date = 2007-03-09 }}

</ref>

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=== Use as clustering algorithm ===

As VQ is seeking for centroids as density points of nearby lying samples, it can be also directly used as a prototype-based clustering method: each centroid is then associated with one prototype.

By aiming to minimize the expected squared quantization error<ref>{{cite journal|last=Gray|first=R.M.|title=Vector Quantization|journal=IEEE ASSP Magazine|year=1984|volume=1|issue=2|pages=4–29|doi=10.1109/massp.1984.1162229|hdl=2060/19890012969|hdl-access=free}}</ref> and introducing a decreasing learning gain fulfilling the Robbins-Monro conditions, multiple iterations over the whole data set with a concrete but fixed number of prototypes converges to the solution of [[k-means]] clustering algorithm in an incremental manner.

=== Generative Adversarial Networks (GAN) ===

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==External links==

* http://www.data-compression.com/vq.html {{Webarchive|url=https://web.archive.org/web/20171210201342/http://www.data-compression.com/vq.html |date=2017-12-10 }}

* [httphttps://qccpack.sourceforge.net QccPack — Quantization, Compression, and Coding Library (open source)]

* [https://dl.acm.org/citation.cfm?id=1535126 VQ Indexes Compression and Information Hiding Using Hybrid Lossless Index Coding], Wen-Jan Chen and Wen-Tsung Huang