PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Noise reduction, smoothing and time interval segmentation of noisy signals using an energy optimisation method
Sasan Mahmoodi and Bayan Sharif
IEE Proceedings Vision, Image and Signal Processing Volume 153, Number 2, pp. 101-108, 2004.

Abstract

Noise reduction and time interval segmentation of a noise-contaminated piecewise continuous signal is considered by the authors as a non-linear optimisation problem. The mathematical framework of this method is presented both in continuous-time and discrete-time domains. The smoothed signal and segmented time intervals of the original noisy signal are calculated as an optimised solution for an energy functional. An algorithm similar to the level set method is developed to find the optimised solution. In this algorithm, the discontinuity points separating consecutive continuous signals are preserved while the noise is reduced. Therefore this method fundamentally exhibits a better performance compared with a traditional low-pass filter suppressing high frequency components, including discontinuity points. The results also demonstrate a better quality in noise reduction in comparison to the median and Gaussian filters.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:4242
Deposited By:Sasan Mahmoodi
Deposited On:20 December 2008