EMBEDDING DIFFUSION IN VARIATIONAL BAYES: A TECHNIQUE FOR SEGMENTING IMAGES

EMBEDDING DIFFUSION IN VARIATIONAL BAYES: A TECHNIQUE FOR SEGMENTING IMAGES

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by Giuseppe Boccignone , Paolo Napoletano , Mario Ferraro

BibTeX

@MISC{Boccignone_embeddingdiffusion,
    author = {Giuseppe Boccignone and Paolo Napoletano and Mario Ferraro},
    title = {EMBEDDING DIFFUSION IN VARIATIONAL BAYES: A TECHNIQUE FOR SEGMENTING IMAGES},
    year = {}
}

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Abstract

In this paper, we discuss how image segmentation can be handled by using Bayesian learning and inference. In particular variational techniques relying on free energy minimization will be introduced. It will be shown how to embed a spatial diffusion process on segmentation labels within the Variational Bayes learning procedure so as to enforce spatial constraints among labels.

Citations

759	Information Theory, Inference and Learning Algorithms - Mackay - 2003
533	Computer Vision: A Modern Approach - Forsyth, Ponce - 2002
181	Variational algorithms for approximate Bayesian inference - Beal - 2003
151	Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm - Zhang, Brady, et al. - 2001
147	Image segmentation by data-driven Markov chain Monte Carlo - Tu, Zhu - 2002
40	M.: Toward Objective Evaluation of Image Segmentation Algorithms - Unnikrishnan, Pantofaru, et al.
33	A comparison of algorithms for inference and learning in probabilistic graphical models - Frey, Jojic - 2005
31	Color Image Segmentation: A State-of-the-Art Survey - Lucchese, Mitra
27	Variational Bayesian model selection for mixture distributions - Corduneanu, Bishop - 2001
23	Probabilistic models of cognition: Conceptual foundations. Trends in Cognitive Sciences - Chater, Tenenbaum, et al. - 2006
22	Quantitative Methods of Evaluating Image Segmentation - Huang, Dom - 1995
20	Applications of nonlinear diffusion in image processing and computer vision - Weickert
16	ter Haar Romeny and - Weickert, M - 1998
13	ªOn the Representation of Image Structures via Scale Space Entropy Conditionsº - Ferraro, Boccignone, et al. - 1999
12	Variational bayes for d-dimensional Gaussian mixture models - Penny - 2001
8	Variational learning for Gaussian mixture models - Nasios, Bors
4	Variational Bayes inference of spatial mixture models for segmentation - Woolrich, Behrens
3	Bayesian Pixel Classification using Spatially Variant Finite Mixures and (a) (b) (c) Fig. 4. (a) Original image. textured (b) Image treated by the proposed algorithm. (c) Image SR. treated by Generalised EM Algorithm - Gopal, Hebet - 1998
2	An information--theoretic approach to interactions in images - Boccignone, Ferraro - 1999
1	Encoding visual information from anisotropic transformations - Boccignone, Ferraro, et al.
1	A variational Bayes approach to image segmentation - Boccignone, Ferraro, et al.