1887

Abstract

Summary

Radon transforms are integral operators widely used in seismic exploration for multiple attenuation, velocity analysis and data interpolation. A reasonable assumption about the Radon transform applied to seismic images is sparseness, where the image energy focuses into clusters in the Radon model space. In this paper we apply the Weak Orthogonal Matching Pursuit framework (WOMP) to exploit sparseness and implement a High Resolution Radon Transform: in particular, we introduce a new automatic selection criterion for the Weak Orthogonal Matching Pursuit algorithm based on the physical model underlying the problem (called GeOMP). Results on real data prove the effectiveness of the method over general purpose selection criteria in terms of both reconstruction quality and decreased computational cost.

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/content/papers/10.3997/2214-4609.20141568
2014-06-16
2024-04-25
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References

  1. M.D.Sacchi and T.J.Ulrych
    , High-resolution velocity gathers and offset space reconstruction, Geophysics, vol. 4, n. 60, pp. 1169–1177, Jul1995.
    [Google Scholar]
  2. WangJ., NgM., and PerzM.
    , Seismic data interpolation by greedy local radon transform, Geophysics, n. 75, 2010.
    [Google Scholar]
  3. RemiGribonval and MortenNielsen
    , Approximate weak greedy algorithms, Adv. Comput. Math., vol. 14, n. 4, pp. 361–378, 2001.
    [Google Scholar]
  4. David L.Donoho, YaakovTsaig, IddoDrori, and Jean-LucStarck
    , Sparse solution of underdetermined systems of linear equations by stagewise orthogonal matching pursuit, IEEE Transactions on Information Theory, vol. 58, no. 2, pp. 1094–1121, 2012.
    [Google Scholar]
  5. ThomasBlumensath and Mike E.Davies
    , Stagewise weak gradient pursuits part i: Fundamentals and numerical studies, Trans. Sig. Proc., vol. 57, no. 11, Nov.2009.
    [Google Scholar]
  6. DeannaNeedell and RomanVershynin
    , Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit, J. Sel. Topics Signal Processing, vol. 4, no. 2, pp. 310–316, 2010.
    [Google Scholar]
  7. AlesandrShnayderman, AlexanderGusev, and Ahmet M.Eskicioglu
    , An svd-based gray-scale image quality measure for local and global assessment, IEEE Transaction on Image Processing, 2006.
    [Google Scholar]
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