Bulletin of the Seismological Society of America
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


Bulletin of the Seismological Society of America; February 2009; v. 99; no. 1; p. 226-234; DOI: 10.1785/0120080001
© 2009 Seismological Society of America
This Article
Right arrow Figures Only
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Electronic Supplement
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Parolai, S.
Right arrow Search for Related Content
GeoRef
Right arrow GeoRef Citation

Denoising of Seismograms Using the S Transform

Stefano Parolai

Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Telegrafenberg 14473 Potsdam, Germany

Online Material: Illustration of the denoising of seismograms using the S transform.

The growing number of urban seismological experiments within the framework of seismic hazard studies has increased the necessity of effective tools for denoising seismograms. Because of the frequency dependency of seismic noise and the nonstationarity of the recorded signal, tools that can effectively take into account the frequency-time variation of the seismic recordings are more suitable for fulfilling this task. The S transform is an invertible time-frequency spectral localization technique that combines elements of wavelet transforms and short-time Fourier transforms. In this study, a customized thresholding technique is applied to the S-transform coefficients for obtaining an optimally (in the sense of the maximum increase of the signal-to-noise ratio with a minimal loss of information) denoised seismogram. Tests performed with synthetic data allow us to calibrate the optimal denoising procedure parameters and show the effectiveness of the proposed method when compared with standard filtering techniques. The application of a combination of denoising with time-frequency filtering on real data shows the potential of the method for extracting lower amplitude dispersive arrivals from seismograms.







HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2009 by the Seismological Society of America.