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Improved hidden Markov models in the wavelet-domain

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2 Author(s)
Guoliang Fan ; Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA ; Xiang-Gen Xia

Wavelet-domain hidden Markov models (HMMs), in particular the hidden Markov tree (HMT) model, have been introduced and applied to signal and image processing, e.g., signal denoising. We develop a simple initialization scheme for the efficient HMT model training and then propose a new four-state HMT model called HMT-2. We find that the new initialization scheme fits the HMT-2 model well. Experimental results show that the performance of signal denoising using the HMT-2 model is often improved over the two-state HMT model developed by Crouse et al. (see ibid., vol.46, p.886-902, 1998)

Published in:

Signal Processing, IEEE Transactions on  (Volume:49 ,  Issue: 1 )