Bayes factors for edge detection from wavelet product spaces

Fionn Murtagh, Jean Luc Starck

Research output: Contribution to journalReview articlepeer-review

7 Citations (Scopus)


Interband wavelet correlation provides one approach to defining edges in an image. Interband wavelet products follow long-tailed density distributions, and in such a context thresholding is very difficult. We show how segmentation using a Markov-field spatial dependence model is a more appropriate approach to demarcating edge and non-edge regions. A key part of this work is quantitative assessment of goodness of edge versus nonedge fit. We introduce a formal assessment framework based on Bayes factors. A detailed example is used to illustrate these results.

Original languageEnglish
Pages (from-to)1375-1382
Number of pages8
JournalOptical Engineering
Issue number5
Publication statusPublished - 1 May 2003
Externally publishedYes


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