Wavelet-Based Image Denoising Using Hidden Markov Models

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Wavelet-Based Image Denoising Using Hidden Markov Models
Wavelet-domain hidden Markov models (HMMs) have been recently proposed and applied to image processing, e.g., image denoising. In this paper, we develop a new HMM, called local contextual HMM (LCHMM), by introducing the Gaussian mixture field where wavelet coefficients are assumed to locally follow the Gaussian mixture distributions determined by their neighborhoods. The LCHMM can exploit both the local statistics and the intrascale dependencies of wavelet coefficients at low computational complexity. We show that the proposed LCHMM combined with the “Cycle-spinning” technique may achieve the best performance in image denoising.
Guoliang Fan, Xiang-Gen Xia
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Where ICIP
Authors Guoliang Fan, Xiang-Gen Xia
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