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bayesian analysis

Bayesian image analysis in Fourier space (BIFS) models and some relationships with Markov random fields

Prof. John Kornak, Biostatistics, University of California, San Francisco

Oct 14, 16:30 - 17:45

B4 B5 A0215

bayesian analysis

Abstract For over 30 years, Bayesian image analysis has provided an important pathway to image reconstruction and enhancement, by balancing a priori expectations of image characteristics with a model for the noise process. The conventional Bayesian modeling approach defined in image space implements priors that describe inter-dependence between spatial locations (and can therefore be difficult to model and compute). However, similar models can be developed more conveniently in Fourier transformed space as a large set of independent processes. The originally complex high-dimensional estimation

Biostatistics Group (BIOSTATS)

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