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The Partitioned Mixture Distribution: Multiple Overlapping Density Models

  • Stephen P Luttrell
Conference paper
  • 284 Downloads
Part of the Fundamental Theories of Physics book series (FTPH, volume 70)

Abstract

In image processing problems density models are often used to characterise the local image statistics. In this paper a layered network structure is proposed, which consists of a large number of overlapping mixture distributions. This type of network is called a partitioned mixture distribution (PMD), and it may be used to apply mixture distribution models simultaneously to many different patches of an image.

Keywords

Expectation Maximisation Relative Entropy Expectation Maximisation Algorithm Predictive Distribution Mixture Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    S. P. Luttrell, “The partitioned mixture distribution: an adaptive Bayesian network for low-level image processing”, IEE Proceedings on Vision, Image and Signal Processing, Vol. 141, No. 4,pp: 251 – 260, 1994.CrossRefGoogle Scholar
  2. [2]
    D. M. Titterington, A. F. M. Smith and U. E. Makov, “Statistical analysis of finite mixture distributions”, Wiley, 1985.zbMATHGoogle Scholar
  3. A. P. Dempster, N. M. Laird and D. B. Rubin, “Maximum likelihood from incomplete data via the EM algorithm”, Journal of the Royal Statistical Society Series B, Vol. 39,pp: 1 – 37, 1977.MathSciNetzbMATHGoogle Scholar
  4. S. P. Luttrell, “An adaptive Bayesian network for low-level image processing”, Proceedings of the 3rd IEE International Conference on Artificial Neural Networks, Brighton,pp: 61 – 65, 1993.Google Scholar

Copyright information

© British Crown Copyright 1994

Authors and Affiliations

  • Stephen P Luttrell
    • 1
  1. 1.Defence Research AgencyWorcestershireUK

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