Quick Search:    advanced search

GSW Home   GeoRef Home   My GSW Alerts   Contact GSW   About GSW   Journals List   Help

This Article Figures Only Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (4) Citing Articles via Google Scholar Google Scholar Articles by Galiana-Merino, J. J. Articles by Botella, F. Search for Related Content GeoRef GeoRef Citation

De-Noising of Short-Period Seismograms by Wavelet Packet Transform

Departamento de Fisica, Ingeniería de Sistemas y Teoría de la Señal
Escuela Politécnica Superior
Universidad de Alicante
Ap. Correos 99, 03080 Alicante, Spain
(J.J.G.-M., J.R.-H.)
Departamento de Ciencias de la Tierra y del Medio Ambiente
Facultad de Ciencias
Universidad de Alicante
Ap. Correos 99, 03080 Alicante, Spain
(J.G., S.M.)
Centro de Investigación Operativa
Universidad Miguel Hernández
Avda. Ferrocarril, s/n, 03202 Elche, Spain
(F.B.)

Manuscript received 5 March 2001.

The wavelet packet transform gives information in both the time and frequency domains, and it is very useful for describing nonstationary signals like seismograms. Moreover, this structure is dependent on the signal under study; hence we can choose the time-frequency decomposition more appropriate for every signal. In this article, we propose a new method for filtering based on the wavelet packet transform. This approach uses different parameters for filtering, depending on the band of frequencies that we are analyzing. This filtering is employed in order to achieve a high signal-to-noise ratio (SNR) and low distortion. We first apply the method to synthetic signals that we have contaminated with noise. In this way, the shape of the whole output signal and the onset time of the first pulse can be compared to the ideal signal. Finally, we apply it to short-period seismograms recorded at the local seismic network of the University of Alicante in southeastern Spain. The method proposed is compared with conventional passband filters and other methods based on wavelets. The comparison demonstrates that our method achieves a higher SNR without introducing noticeable distortion.

This article has been cited by other articles:

				S. Parolai Denoising of Seismograms Using the S Transform Bulletin of the Seismological Society of America, February 1, 2009; 99(1): 226 - 234. [Abstract] [Full Text] [PDF]

				J. J. Galiana-Merino, J. Rosa-Herranz, P. Jauregui, S. Molina, and J. Giner Wavelet Transform Methods for Azimuth Estimation in Local Three-Component Seismograms Bulletin of the Seismological Society of America, June 1, 2007; 97(3): 793 - 803. [Abstract] [Full Text] [PDF]

				S. Parolai and J. J. Galiana-Merino Effect of Transient Seismic Noise on Estimates of H/V Spectral Ratios Bulletin of the Seismological Society of America, February 1, 2006; 96(1): 228 - 236. [Abstract] [Full Text] [PDF]

				Regularized Deconvolution of Local Short-Period Seismograms in the Wavelet Packet Domain Bulletin of the Seismological Society of America, August 1, 2004; 94(4): 1467 - 1475.