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

Authors:
Sasan Mahmoodi;Bayan S. Sharif
Affiliations:
Psychology Department, School of Biology, Newcastle University, Newcastle upon Tyne, UK;School of Electrical, Electronic and Computer Engineering, Merz Court, Newcastle University, Newcastle upon Tyne, UK
Venue:
Signal Processing - Special section: Distributed source coding
Year:
2006

Citing 9
Cited 0

Advanced Engineering Mathematics: Maple Computer Guide

Advanced Engineering Mathematics: Maple Computer Guide
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model

International Journal of Computer Vision
A level set algorithm for minimizing the Mumford-Shah functional in image processing

VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
An Inexact Newton-CG-Type Active Contour Approach for the Minimization of the Mumford-Shah Functional

Journal of Mathematical Imaging and Vision
Signal segmentation and denoising algorithm based on energy optimisation

Signal Processing
Nonlinear optimisation method for image segmentation and noise reduction using geometrical intrinsic properties

Image and Vision Computing
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations

Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations
Active contours without edges

IEEE Transactions on Image Processing
Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

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.