Image and Signal Restoration Using Pairwise Markov Trees
نویسندگان
چکیده
This work deals with the statistical restoration of a hidden signal using Pairwise Markov Trees (PMT). PMT have been introduced recently in the case of a discrete hidden signal. We first show that PMT can perform better than the classical Hidden Markov Trees (HMT) when applied to unsupervised image segmentation. We next consider a PMT in a linear Gaussian model with continuous hidden data, and we give formulas of an original extension of the classical Kalman filter.
منابع مشابه
A Multiscale Smoothing Algorithm for Pairwise Markov Trees
An important problem in multiresolution analysis of signals and images consists in restoring continuous hidden random variables x = {xs}s∈S from observed ones y = {ys}s∈S . This is done classically in the context of Hidden Markov Trees (HMT). HMT have been generalized recently to Pairwise Markov Trees (PMT). In this paper we propose a smoothing restoration algorithm for Gaussian PMT.
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