Texture image segmentation using Brushlet-domain hidden Markov models
2009
By researching the Brushlet domain coefficients of texture images, we found that the distribution of the magnitudes of
Brushlet domain coefficients roughly meet rayleigh distribution. And there are correlations between Brushlet coefficients
in adjacent scales. Therefore, Rayleigh Mixture Model (RMM) is used to characterize the statistics of the magnitudes of
Brushlet coefficients. To capture the inter-scale persistence of Brushlet coefficients, a "four to four" models with markov
property is adopted in this paper. On the basis, by combining with the multi-scale Bayesian segmentation method, we
propose a multiscale Bayesian texture segmentation algorithm that is based on a Brushlet domain hidden Markov tree
(BruHMT) model. The experiment results indicate that our method is feasible and effective. Especially for coarse texture,
our method is superior than texture segmentation method using Wavelet domain hidden Markov tree (WHMT) model.
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