Smoothers for Discontinuous Signals

Winkler, Gerhard and Liebscher, V. and Aurich, Volker (1999): Smoothers for Discontinuous Signals. Collaborative Research Center 386, Discussion Paper 146

Abstract

First we explain the interplay between robust loss functions, nonlinear filters and Bayes smoothers for edge-preserving image reconstruction. Then we prove the surprising fact that maximum posterior smoothers are nonlinear filters. A (generalized) Potts prior for segmentation and piecewise smoothing of noisy signals and images is adopted. For one-dimensional signals, an exact solution for the maximum posterior mode - based on dynamic programming - is derived. After some results on the performance of nonlinear filters on jumps and ramps we finally introduce a cascade of nonlinear filters with varying scale parameters and discuss the choice of parameters for segmentation and piecewise smoothing.

• Item Type: Paper (Research Paper)
• Keywords: Image processing, jump preserving smoothing, filters, Potts model
• Collections: Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386; Special Research Fields > Special Research Field 386
• Subjects: 500 Science > 510 Mathematics
• Language: English