Bayesian multiscale analysis of images modeled as Gaussian Markov random fields
Journal article, Peer reviewed
Permanent lenke
http://hdl.handle.net/11250/259121Utgivelsesdato
2012Metadata
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Originalversjon
10.1016/j.csda.2011.07.009Sammendrag
A Bayesian multiscale technique for detection of statistically significant features in noisy images is proposed. The prior is defined as a stationary intrinsic Gaussian Markov random field on a toroidal graph, which enables efficient computation of the relevant posterior marginals. Hence the method is applicable to large images produced by modern digital cameras. The technique is demonstrated in two examples from medical imaging.