DPA: A Deterministic Approach to the MAP Problem

Marc Berthod, Zoltan Kato, Josiane Zerubia

Research output: Contribution to journalArticle

8 Citations (Scopus)


Deterministic pseudo-annealing (DPA) is a new deterministic optimization method for finding the maximum a posteriori (MAP) labeling in a Markov random field, in which the probability of a tentative labeling is extended to a merit function on continuous labelings. This function is made convvex by changing its definition domain. This unambiguous maximization problem is solved, and the solution is followed down to the original domain, yielding a good, if suboptimal, solution to the original labeling assignment problem. The performance of DPA is analyzed on randomly weighted graphs.

Original languageEnglish
Pages (from-to)1312-1314
Number of pages3
JournalIEEE Transactions on Image Processing
Issue number9
Publication statusPublished - Sep 1995

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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