抄録
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.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 1312-1315 |
| ページ数 | 4 |
| ジャーナル | IEICE Transactions on Information and Systems |
| 巻 | E92-D |
| 発行部数 | 6 |
| DOI | |
| 出版物ステータス | Published - 2009 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Software
- Artificial Intelligence
- Hardware and Architecture
- Computer Vision and Pattern Recognition
これを引用
Estimation of optimal parameter in ε-filter based on signal-noise decorrelation. / Matsumoto, Mitsuharu; Hashimoto, Shuji.
：: IEICE Transactions on Information and Systems, 巻 E92-D, 番号 6, 2009, p. 1312-1315.研究成果: Article
}
TY - JOUR
T1 - Estimation of optimal parameter in ε-filter based on signal-noise decorrelation
AU - Matsumoto, Mitsuharu
AU - Hashimoto, Shuji
PY - 2009
Y1 - 2009
N2 - 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.
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.
KW - ε-filter
KW - Nonlinear filter
KW - Parameter optimization
UR - http://www.scopus.com/inward/record.url?scp=77950193067&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950193067&partnerID=8YFLogxK
U2 - 10.1587/transinf.E92.D.1312
DO - 10.1587/transinf.E92.D.1312
M3 - Article
AN - SCOPUS:77950193067
VL - E92-D
SP - 1312
EP - 1315
JO - IEICE Transactions on Information and Systems
JF - IEICE Transactions on Information and Systems
SN - 0916-8532
IS - 6
ER -