PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A nonlinear variational method for signal segmentation and reconstruction using level set algorithm
Sasan Mahmoodi and Bayan Sharif
Signal Processing Volume 86, pp. 3496-3504, 2005.

Abstract

A nonlinear functional is considered in this letter for segmentation and noise removal of piecewise continuous signals containing binary information contaminated with Gaussian noise. A discontinuity is defined as points in time scale that separates two signal segments with different amplitude spectra. Segmentation and noise removal of a piecewise continuous signal are obtained by deriving equations minimising the nonlinear functional. An algorithm based on the level set method is employed to implement the solutions minimising the functional. The proposed method is robust in noisy signals and can avoid local minima.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:4244
Deposited By:Sasan Mahmoodi
Deposited On:20 December 2008