Texture analysis with variational hidden Markov trees


Journal Article

A variational Bayes formulation of the hidden Markov tree (HMT) model is proposed for texture analysis, utilizing a multilevel wavelet decomposition of imagery. The variational method yields an approximation to the full posterior of the HMT parameters. Texture classification is based on the posterior predictive distribution or marginalized evidence, with example results presented. © 2006 IEEE.

Full Text

Duke Authors

Cited Authors

  • Dasgupta, N; Carin, L

Published Date

  • June 1, 2006

Published In

Volume / Issue

  • 54 / 6 I

Start / End Page

  • 2352 - 2356

International Standard Serial Number (ISSN)

  • 1053-587X

Digital Object Identifier (DOI)

  • 10.1109/TSP.2006.872588

Citation Source

  • Scopus