期刊
JOURNAL OF NONPARAMETRIC STATISTICS
卷 14, 期 1-2, 页码 203-222出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/10485250211388
关键词
signal processing; image analysis; edge preserving smoothing; nonlinear filters; Potts model
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.
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