Noise reduction based on cross TF ε-filter

Tomomi Abe*, Mitsuharu Matsumoto, Shuji Hashimoto

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    A time-frequency ε-filter (TF ε-filter) is an advanced ε-filter applied to complex spectra along the time axis. It can reduce most kinds of noise while preserving a signal that varies frequently such as a speech signal. The filter design is simple and it can effectively reduce noise. It is applicable not only to small amplitude stationary noise but also to large amplitude nonstationary noise. However when we consider the noise that varies much frequently along the time axis, TF ε-filter cannot reduce noise without the signal distortion. When we consider the noise where the neighboring frequency bins have similar powers such as impulse noise, we can reduce the noise by using ε-filter applied to the complex spectra not along the time axis, but along the frequency axis. This paper introduces an advanced method for noise reduction that applies ε-filter to complex spectra not only along the time axis but also along the frequency axis labeled cross TF ε-filter. We conducted the experiments utilizing the sounds with stationary, nonstationary and natural noise.

    Original languageEnglish
    Title of host publicationSIGMAP 2008 - Proceedings of the International Conference on Signal Processing and Multimedia Applications
    Pages105-112
    Number of pages8
    Publication statusPublished - 2008
    EventSIGMAP 2008 - International Conference on Signal Processing and Multimedia Applications - Porto
    Duration: 2008 Jul 262008 Jul 29

    Other

    OtherSIGMAP 2008 - International Conference on Signal Processing and Multimedia Applications
    CityPorto
    Period08/7/2608/7/29

    Keywords

    • ε-filter
    • Noise reduction
    • Speech enhancement
    • Time-frequency domain

    ASJC Scopus subject areas

    • Computer Graphics and Computer-Aided Design
    • Signal Processing

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