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Abstract

Summary

Random noises corrupt the information contained in seismic data and in order to obtain more reliable information we have to attenuate them as much as possible. The majority of methods by using an appropriate transformation do this task. But in this paper we do not use any transformation domain and introduce two temporal/spatial filters named Bilateral and Non-local means. After comparative study of their performance on synthetic data, we address the problem of parameter estimation for the proposed filters and present a method to estimate the optimal parameters. The synthetic data test shows high performance of our method.

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/content/papers/10.3997/2214-4609.20141324
2014-06-16
2024-03-28
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References

  1. Almeida, M. and Figueiredo, M.
    [2013] Parameter estimation for blind and non-blind deblurring using residual whiteness measure, IEEE Trans. on image processing(to appear).
    [Google Scholar]
  2. Bonar, D. and Sacchi, M.
    [2012] Denoising seismic data using the nonlocal means algorithm. Geophysics, 77(1), A5–A8.
    [Google Scholar]
  3. HansenP.C.
    [1999] Rank-deficient and discrete ill-posed problems: numerical aspects of linear Inversion. SIAM, Philadelphia. USA.
    [Google Scholar]
  4. Neelamani, R., Baumstein, A.I., Gillard, D.G., Hadidi, M.T. and Soroka, W.I.
    [2008] Coherent and random noise attenuation using the curvelet transform. The Leading Edge, 27, 240–248.
    [Google Scholar]
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