Optimal nonlinear filter to remove random impulses from Gaussian noise
Optimal nonlinear filter to remove random impulses from Gaussian noise
This paper investigates the problem of removing random impulse noise from a white signal of Gaussian distribution. A nonlinear polynomial filter is used, whose coefficients are optimised using an exact least squares method. The method relies on exploiting the differing probability distributions of the impulsive noise and the Gaussian signal. The paper then looks at the effect of both the polynomial order and the normalised spike amplitude on the mean squared error and signal to noise ratio. The results are compared to the results found using a simple clipping filter. The results show that the optimal filter gives a much improved performance over the simple clipping filter in reducing the mean square error.
gaussian distribution, gaussian noise, impulse noise, least mean squares methods, nonlinear filters, optimisation, polynomial matrices, random noise, signal processing
1541-1544
Notley, S.V.
3a5a223e-3123-41b9-b7ae-65dfcb20d782
Harte, J.M.
20107083-3305-4997-8426-0372ff0b9954
Elliott, S.J.
721dc55c-8c3e-4895-b9c4-82f62abd3567
2002
Notley, S.V.
3a5a223e-3123-41b9-b7ae-65dfcb20d782
Harte, J.M.
20107083-3305-4997-8426-0372ff0b9954
Elliott, S.J.
721dc55c-8c3e-4895-b9c4-82f62abd3567
Notley, S.V., Harte, J.M. and Elliott, S.J.
(2002)
Optimal nonlinear filter to remove random impulses from Gaussian noise.
In IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002 (ICASSP '02): proceedings.
IEEE.
.
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Conference or Workshop Item
(Paper)
Abstract
This paper investigates the problem of removing random impulse noise from a white signal of Gaussian distribution. A nonlinear polynomial filter is used, whose coefficients are optimised using an exact least squares method. The method relies on exploiting the differing probability distributions of the impulsive noise and the Gaussian signal. The paper then looks at the effect of both the polynomial order and the normalised spike amplitude on the mean squared error and signal to noise ratio. The results are compared to the results found using a simple clipping filter. The results show that the optimal filter gives a much improved performance over the simple clipping filter in reducing the mean square error.
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Published date: 2002
Venue - Dates:
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002 (ICASSP '02), Orlando, USA, 2002-05-13 - 2002-05-17
Keywords:
gaussian distribution, gaussian noise, impulse noise, least mean squares methods, nonlinear filters, optimisation, polynomial matrices, random noise, signal processing
Identifiers
Local EPrints ID: 10922
URI: http://eprints.soton.ac.uk/id/eprint/10922
PURE UUID: 8ba66a9c-586f-4f3c-80a2-0572e89a3c55
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Date deposited: 13 Jun 2005
Last modified: 05 Mar 2024 17:37
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Contributors
Author:
S.V. Notley
Author:
J.M. Harte
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