Smoothers for Discontinuous Signals

Author: G. Winkler

Source: Journal of Nonparametric Statistics, Volume 14, Numbers 1-2, Numbers 1-2/2002 , pp. 203-222(20)

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Abstract:

We discuss the interplay between local M-smoothers, Bayes smoothers and some nonlinear filters for edge-preserving signal reconstruction. We prove that all smoothers in question are nonlinear filters in a precise sense and characterize their fixed points. Then a Potts model is adopted for segmentation. For 1-d signals, an exact algorithm for the computation of maximum posterior modes is derived and applied to a phantom and to 1-d fMRI-data.

Keywords: Signal processing; Image analysis; Edge preserving smoothing; Nonlinear filters; Potts model

Document Type: Research article

DOI: http://dx.doi.org/10.1080/10485250211388

Publication date: 2002-01-01