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Pré-Publication, Document De Travail Année : 2016

Cut Pursuit: fast algorithms to learn piecewise constant functions on general weighted graphs

Résumé

We propose working-set/greedy algorithms to efficiently solve problems penalized respectively by the total variation on a general weighted graph and its L0 counterpart the Mumford Shah total level-set boundary size when the piecewise constant solutions have a small number of distinct level-sets; this is typically the case when the total level-set boundary size is small, which is encouraged by these two forms of penalization. Our algorithms exploit this structure by recursively splitting the level-sets of a piecewise-constant candidate solution using graph cuts. We obtain significant speed-ups over state-of-the-art algorithms for images that are well approximated with few level-sets
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Dates et versions

hal-01306779 , version 1 (26-04-2016)
hal-01306779 , version 2 (18-01-2017)
hal-01306779 , version 3 (31-07-2017)
hal-01306779 , version 4 (21-08-2017)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

  • HAL Id : hal-01306779 , version 2

Citer

Loic Landrieu, Guillaume Obozinski. Cut Pursuit: fast algorithms to learn piecewise constant functions on general weighted graphs. 2016. ⟨hal-01306779v2⟩
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