Quantization from Bayes factors with application to multilevel thresholding

F. Murtagh, J. L. Starck

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


We are concerned with the optimal selection of multiple thresholds in image analysis. We propose the use of the Bayes information criterion, a minimal information measure, for this and illustrate its use in practical cases. Applications of multiple threshold selection of interest to us include the closely related problems of (i) quantization for lossy encoding, and (ii) segmentation. Our examples relate to segmentation as a post-processing phase in edge detection.

Original languageEnglish
Pages (from-to)2001-2007
Number of pages7
JournalPattern Recognition Letters
Issue number12
Early online date25 Mar 2003
Publication statusPublished - 1 Aug 2003
Externally publishedYes


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