A nonlinear variational method for signal segmentation and reconstruction using level set algorithm

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 spectr...

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Bibliographic Details
Published in:Signal processing 2006-11, Vol.86 (11), p.3496-3504
Main Authors: Mahmoodi, Sasan, Sharif, Bayan S.
Format: Article
Language:English
Subjects:
Applied sciences
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Information, signal and communications theory
Level set method
Miscellaneous
Nonlinear optimisation
Signal and communications theory
Signal processing
Signal reconstruction
Signal segmentation
Signal, noise
Telecommunications and information theory
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Summary: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.
ISSN:0165-1684
1872-7557
DOI:10.1016/j.sigpro.2006.06.012