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
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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 -