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A study of contextual modeling and texture characterization for multiscale Bayesian segmentation

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2 Author(s)
Guoliang Fan ; Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK, USA ; Xiaomu Song

In this paper, we demonstrate that multiscale Bayesian image segmentation can be enhanced by improving both contextual modeling and statistical texture characterization. Firstly, we show a joint multi-context and multiscale approach to achieve more robust contextual modeling by using multiple context models. Secondly, we study statistical texture characterization using wavelet-domain hidden Markov models (HMMs), and in particular, we use an improved HMM, HMT-3S, to obtain more accurate multiscale texture characterization. Experimental results show that both of them play important roles in multiscale Bayesian segmentation.

Published in:

Image Processing. 2002. Proceedings. 2002 International Conference on  (Volume:3 )

Date of Conference:

24-28 June 2002