Random noise attenuation using a structure-oriented weighted singular value decomposition
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geochemistry and Petrology,Geophysics
Link
http://link.springer.com/content/pdf/10.1007/s11200-019-0723-8.pdf
Reference38 articles.
1. Bekara M. and Mirko V.D.B., 2007. Local singular value decomposition for signal enhancement of seismic data. Geophysics, 72, V59–V65.
2. Cai H., He Z. and Huang, D., 2011. Seismic data denoising based on mixed time-frequency methods. Appl. Geophys., 8, 319–327.
3. Chen Y., 2017. Fast dictionary learning for random noise attenuation of multidimensional seismic data. Geophys. J. Int., 209, 21–31.
4. Chen Y., Gan S., Liu T., Yuan J., Zhang Y. and Jin Z., 2014. Random noise attenuation by a selective hybrid approach using f-x empirical mode decomposition. J. Geophys. Eng., 12, 12–25.
5. Chen Y., Huang W., Zhou Y., Liu W. and Zhang D., 2018. Plane-wave orthogonal polynomial transform for amplitude-preserving noise attenuation. Geophys. J. Int., 214, 2207–2223.
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1. Modified non-local means: A novel denoising approach to process gravity field data;Open Geosciences;2023-01-01
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3. Velocity analysis of noisy seismic data based on RSVD weighted semblance;Studia Geophysica et Geodaetica;2022-04
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