IOP Conference Series Earth and Environmental Science · 2021 · 11 citations · 4 references
Natural SciencesGeophysicsEarthquake EngineeringSeismologyTime Series AnalysisDigital Signal ProcessingGeophysical Data ProcessingGeophysical Signal ProcessingSeismic Data ProcessingSeismic ImagingSignal ProcessingEmpirical Mode DecompositionSeismic Data DenoisingSeismic Signal ProcessingSignal DecompositionSignal DenoisingSignal-to-noise EnhancementSignal-to-noise RatioWavelet Denoising
Abstract Seismic data usually contains a lot of noise. In order to effectively remove noise and improve the signal-to-noise ratio of seismic signals, this paper proposes a method of combining complete empirical mode decomposition (CEEMD) with improved wavelet threshold denoising.method. CEEMD has good adaptability to signal decomposition; the new wavelet threshold function can effectively overcome the discontinuity of hard threshold function and the deviation of wavelet coefficients in soft threshold function. The combination of the two methods can obtain better denoising effect. After processing the simulated signal with the method proposed in this paper, the signal-to-noise ratio is significantly better than the traditional single denoising method.
4
Norden E. Huang, Steven Long, Man‐Li C. Wu et al. · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 1998 · 23.3K citations · Full text
Computing, Computational Engineering, Biomedical Signal Processing +16
Ideal spatial adaptation by wavelet shrinkage
David L. Donoho, Iain M. Johnstone · Biometrika · 1994 · 7.8K citations