Estimation of optimal parameter in ε-filter based on signal-noise decorrelation

Mitsuharu Matsumoto, Shuji Hashimoto

    Research output: Contribution to journalArticle

    12 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)1312-1315
    Number of pages4
    JournalIEICE Transactions on Information and Systems
    VolumeE92-D
    Issue number6
    DOIs
    Publication statusPublished - 2009

    Keywords

    • ε-filter
    • Nonlinear filter
    • Parameter optimization

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Software
    • Artificial Intelligence
    • Hardware and Architecture
    • Computer Vision and Pattern Recognition

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