Optimal nonlinear filter to remove random impulses from gaussian noise

Scott Notley; James Harte; Stephen Elliot

doi:10.1109/icassp.2002.5744908

Optimal nonlinear filter to remove random impulses from gaussian noise

Scott Notley
, James Harte
, Stephen Elliot

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research

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.

Original language	English
Title of host publication	IEEE International Conference on Acoustics, Speech, and Signal Processing 2002 (ICASSP '02)
Volume	2
Publication date	2002
Pages	1541-1544
DOIs	https://doi.org/10.1109/icassp.2002.5744908
Publication status	Published - 2002
Event	2002 IEEE International Conference on Acoustics, Speech, and Signal Processing - Orlando, United States Duration: 13 May 2002 → 17 May 2002 Conference number: 27

Conference

Conference	2002 IEEE International Conference on Acoustics, Speech, and Signal Processing
Number	27
Country/Territory	United States
City	Orlando
Period	13/05/2002 → 17/05/2002

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@inproceedings{c9670fcd20234182b1dde5f617b908f7,

title = "Optimal nonlinear filter to remove random impulses from gaussian noise",

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.",

author = "Scott Notley and James Harte and Stephen Elliot",

year = "2002",

doi = "10.1109/icassp.2002.5744908",

language = "English",

volume = "2",

pages = "1541--1544",

booktitle = "IEEE International Conference on Acoustics, Speech, and Signal Processing 2002 (ICASSP '02)",

note = "2002 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '02 ; Conference date: 13-05-2002 Through 17-05-2002",

}

Notley, S, Harte, J & Elliot, S 2002, Optimal nonlinear filter to remove random impulses from gaussian noise. in IEEE International Conference on Acoustics, Speech, and Signal Processing 2002 (ICASSP '02). vol. 2, pp. 1541-1544, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing, Orlando, Florida, United States, 13/05/2002. https://doi.org/10.1109/icassp.2002.5744908

TY - GEN

T1 - Optimal nonlinear filter to remove random impulses from gaussian noise

AU - Notley, Scott

AU - Harte, James

AU - Elliot, Stephen

N1 - Conference code: 27

PY - 2002

Y1 - 2002

N2 - 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.

AB - 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.

U2 - 10.1109/icassp.2002.5744908

DO - 10.1109/icassp.2002.5744908

M3 - Article in proceedings

VL - 2

SP - 1541

EP - 1544

BT - IEEE International Conference on Acoustics, Speech, and Signal Processing 2002 (ICASSP '02)

T2 - 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing

Y2 - 13 May 2002 through 17 May 2002

ER -

Optimal nonlinear filter to remove random impulses from gaussian noise

Abstract

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