A generative probabilistic oriented wavelet model for texture segmentation
A generative probabilistic oriented wavelet model for texture segmentation
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Publisher
Dordrecht: Springer
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Language
English
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Publisher
Dordrecht: Springer
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Scope and Contents
Contents
This Letter addresses image segmentation via a generative model approach. A Bayesian network (BNT) in the space of dyadic wavelet transform coefficients is introduced to model texture images. The model is similar to a Hidden Markov model (HMM), but with non-stationary transitive conditional probability distributions. It is composed of discrete hidd...
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Full title
A generative probabilistic oriented wavelet model for texture segmentation
Authors, Artists and Contributors
Author / Creator
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TN_cdi_proquest_journals_2918337956
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2918337956
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ISSN
1370-4621
E-ISSN
1573-773X
DOI
10.1023/A:1026089427119
