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Noise reduction, smoothing and time interval segmentation of noisy signals using an energy optimisation method

Noise reduction, smoothing and time interval segmentation of noisy signals using an energy optimisation method
Noise reduction, smoothing and time interval segmentation of noisy signals using an energy optimisation method
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.
101-108
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Sharif, Bayan
d57a4cae-a6f0-4ab3-b2d8-ef594a75857f
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Sharif, Bayan
d57a4cae-a6f0-4ab3-b2d8-ef594a75857f

Mahmoodi, Sasan and Sharif, Bayan (2006) Noise reduction, smoothing and time interval segmentation of noisy signals using an energy optimisation method. IEE Proceedings - Vision, Image and Signal Processing, 153 (2), 101-108.

Record type: Article

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.

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Published date: April 2006
Organisations: Southampton Wireless Group

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Local EPrints ID: 265863
URI: http://eprints.soton.ac.uk/id/eprint/265863
PURE UUID: ef2096ef-6b18-4b5e-8ed4-af55d15ce085

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Date deposited: 09 Jun 2008 12:43
Last modified: 14 Mar 2024 08:16

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Contributors

Author: Sasan Mahmoodi
Author: Bayan Sharif

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