Unsupervised bayesian convex deconvolution based on a field with an explicit partition function

Details Unsupervised bayesian convex deconvolution based on a field with an explicit partition function Unsupervised bayesian convex deconvolution based on a field with an explicit partition function

2009-01-21

arxiv.org/abs/0901.3326v2

IEEE Trans. Image Processing, vol. 17, no. 1, pp. 16-23, January 2008

Statistics

Methodology

Scientific paper

10.1109/TIP.2007.911819

This paper proposes a non-Gaussian Markov field with a special feature: an explicit partition function. To the best of our knowledge, this is an original contribution. Moreover, the explicit expression of the partition function enables the development of an unsupervised edge-preserving convex deconvolution method. The method is fully Bayesian, and produces an estimate in the sense of the posterior mean, numerically calculated by means of a Monte-Carlo Markov Chain technique. The approach is particularly effective and the computational practicability of the method is shown on a simple simulated example.

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