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Optical Engineering

Bayes factors for edge detection from wavelet product spaces
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Paper Abstract

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 nonedge 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.

Paper Details

Date Published: 1 May 2003
PDF: 8 pages
Opt. Eng. 42(5) doi: 10.1117/1.1564104
Published in: Optical Engineering Volume 42, Issue 5
Show Author Affiliations
Fionn D. Murtagh, Queen's Univ. Belfast (United Kingdom)
Jean-Luc Starck, CEA Saclay (France)

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