Applied Geophysics

, Volume 14, Issue 4, pp 606–619 | Cite as

Translation-invariant wavelet denoising of full-tensor gravity –gradiometer data

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Abstract

Denoising of full-tensor gravity-gradiometer data involves detailed information from field sources, especially the data mixed with high-frequency random noise. We present a denoising method based on the translation-invariant wavelet with mixed thresholding and adaptive threshold to remove the random noise and retain the data details. The novel mixed thresholding approach is devised to filter the random noise based on the energy distribution of the wavelet coefficients corresponding to the signal and random noise. The translationinvariant wavelet suppresses pseudo-Gibbs phenomena, and the mixed thresholding better separates the wavelet coefficients than traditional thresholding. Adaptive Bayesian threshold is used to process the wavelet coefficients according to the specific characteristics of the wavelet coefficients at each decomposition scale. A two-dimensional discrete wavelet transform is used to denoise gridded data for better computational efficiency. The results of denoising model and real data suggest that compared with Gaussian regional filter, the proposed method suppresses the white Gaussian noise and preserves the high-frequency information in gravity-gradiometer data. Satisfactory denoising is achieved with the translation-invariant wavelet.

Keywords

tensor gravity gradiometry denoising threshold translation-invariant wavelet 

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Notes

Acknowledgments

We wish to thank Bell Geospace for the full-tensor gravity-gradient data from the Vinton Dome.

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Copyright information

© Editorial Office of Applied Geophysics and Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Dai-Lei Zhang
    • 1
  • Da-Nian Huang
    • 1
  • Ping Yu
    • 1
  • Yuan Yuan
    • 2
    • 3
  1. 1.College of Geo-Exploration Science and TechnologyJilin UniversityChangchunChina
  2. 2.The Second Institute of Oceanographythe State Oceanic AdministrationHangzhouChina
  3. 3.Key Laboratory of Submarine Geosciencethe State Oceanic AdministrationHangzhouChina

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