In [[image processing]], anAn '''epitome''', in [[data processing]], is a condensed digital representation of the essential [[Statistics|statistical]] properties of ordered [[dataset]]s, such as [[Matrix (mathematics)|matrices]] representingthat imagesrepresent [[image]]s, [[audio signalssignal]]s, videos,[[video]]s or [[genetic sequence]]s. Although much smaller than the epitomized data, the epitome contains many of theits smaller overlapping parts of the data with much less repetition and with some level of generalization. As such, it can be used forin tasks such as [[data mining]], and other [[machine learning]] and [[signal processing tasks. The first ''epitomic analysis'' was performed on image textures<ref>Nebojsa Jojic's image epitome website [http://www.research.microsoft.com/~jojic/epitome.html].</ref> and was used for image parsing. The epitome model has also been applied to videos.<ref>Vincent Cheung's video epitome website [http://www.psi.toronto.edu/~vincent/videoepitome.html].</ref> Filling in missing parts of a video, removing objects from a scene and performing video super-resolution are examples of tasks in which the video epitome has proven useful. Epitomes are also being investigated as tools for rational vaccine design.
The first use of '''epitomic analysis''' was with [[image texture]]s<ref>[http://www.research.microsoft.com/~jojic/epitome.html Nebojsa Jojic's image epitome website]</ref> for the purposes of [[Image processing|image parsing]]. Epitomes have also been used in [[video processing]]<ref>[http://www.vincentcheung.ca/research/videoepitome.html Vincent Cheung's video epitome website]</ref> to replace, remove or [[Superresolution|superresolve]] imagery.
== References ==
Epitomes are also being investigated as tools for [[vaccine design]].{{cn|date=August 2014}}
