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Generalized Edge-Preserving Smoothing for Signal Analysis
Proceedings of the IEEE Workshop on Nonlinear Signal and Image Processing, IEEE, (сентября 1997)
Аннотация
Under the generalized smoothing of a signal, a wider class of operations is understood than the plain suppression of noise. We apply this term to all the processing problems which can be interpreted as those of transformation of the original signal, considered as functions of one discrete argument, into a secondary function of another nature on the same carrier, by way of coordinating the local signal-dependent information and a priori smoothness constraints. In this work, a statistical approach to the generalied edge-preserving smoothing is considered on the basis of treating the sought-for result of processing as a realization of a Markov random process, whose Markov continuity is locally broken at the assumed jump-points. The principal idea of the approach consists in finding the break-points one by one and incorporating them into the model of the hidden process as they are found, so that, at each step, the most detectable of not yet legitimated peculiarities is sought for.
