In this paper, a new multiscale texture segmentation method using contextual hidden Markov tree (CHMT) in wavelet domain is proposed. The hidden Markov tree models (HMT) describe persistence property of wavelet coefficients in multiscale images, but loses clustering property. The method is put forward to overcome the shortcoming of standard HMT by using extended coefficients without changing the wavelet tree structure and makes it possible to get a more accurate segmentation result. Experimental results demonstrate that the proposed method is effective for multiscale texture image segmentation.
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