IEICE TRANSACTIONS on Information
Estimation of Optimal Parameter in ε-Filter Based on Signal-Noise Decorrelation
Summary :
ε-filter is a nonlinear filter for reducing noise and is applicable not only to speech signals but also to image signals. The filter design is simple and it can effectively reduce noise with an adequate filter parameter. This paper presents a method for estimating the optimal filter parameter of ε-filter based on signal-noise decorrelation and shows that it yields the optimal filter parameter concerning a wide range of noise levels. The proposed method is applicable where the noise to be removed is uncorrelated with signal, and it does not require any other knowledge such as noise variance and training data.
- Publication
- IEICE TRANSACTIONS on Information Vol.E92-D No.6 pp.1312-1315
- Publication Date
- 2009/06/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E92.D.1312
- Type of Manuscript
- LETTER
- Category
- Algorithm Theory
Authors
Keyword
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Mitsuharu MATSUMOTO, Shuji HASHIMOTO, "Estimation of Optimal Parameter in ε-Filter Based on Signal-Noise Decorrelation" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 6, pp. 1312-1315, June 2009, doi: 10.1587/transinf.E92.D.1312.
Abstract: ε-filter is a nonlinear filter for reducing noise and is applicable not only to speech signals but also to image signals. The filter design is simple and it can effectively reduce noise with an adequate filter parameter. This paper presents a method for estimating the optimal filter parameter of ε-filter based on signal-noise decorrelation and shows that it yields the optimal filter parameter concerning a wide range of noise levels. The proposed method is applicable where the noise to be removed is uncorrelated with signal, and it does not require any other knowledge such as noise variance and training data.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.1312/_p
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@ARTICLE{e92-d_6_1312,
author={Mitsuharu MATSUMOTO, Shuji HASHIMOTO, },
journal={IEICE TRANSACTIONS on Information},
title={Estimation of Optimal Parameter in ε-Filter Based on Signal-Noise Decorrelation},
year={2009},
volume={E92-D},
number={6},
pages={1312-1315},
abstract={ε-filter is a nonlinear filter for reducing noise and is applicable not only to speech signals but also to image signals. The filter design is simple and it can effectively reduce noise with an adequate filter parameter. This paper presents a method for estimating the optimal filter parameter of ε-filter based on signal-noise decorrelation and shows that it yields the optimal filter parameter concerning a wide range of noise levels. The proposed method is applicable where the noise to be removed is uncorrelated with signal, and it does not require any other knowledge such as noise variance and training data.},
keywords={},
doi={10.1587/transinf.E92.D.1312},
ISSN={1745-1361},
month={June},}
Copy
TY - JOUR
TI - Estimation of Optimal Parameter in ε-Filter Based on Signal-Noise Decorrelation
T2 - IEICE TRANSACTIONS on Information
SP - 1312
EP - 1315
AU - Mitsuharu MATSUMOTO
AU - Shuji HASHIMOTO
PY - 2009
DO - 10.1587/transinf.E92.D.1312
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2009
AB - ε-filter is a nonlinear filter for reducing noise and is applicable not only to speech signals but also to image signals. The filter design is simple and it can effectively reduce noise with an adequate filter parameter. This paper presents a method for estimating the optimal filter parameter of ε-filter based on signal-noise decorrelation and shows that it yields the optimal filter parameter concerning a wide range of noise levels. The proposed method is applicable where the noise to be removed is uncorrelated with signal, and it does not require any other knowledge such as noise variance and training data.
ER -
English
