Application of adaptive iterative low-rank algorithm based on transform domain in desert seismic signal analysis
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Geology,Geophysics,Building and Construction
Link
http://link.springer.com/content/pdf/10.1007/s40328-020-00287-4.pdf
Reference22 articles.
1. Anvari R, Siahsar MAN, Gholtashi S, Roshandel Kahoo A, Mohammadi M (2017) Seismic random noise attenuation using synchrosqueezed wavelet transform and low-rank signal matrix approximation. IEEE Trans Geosci Remote Sens 55(11):6574–6581. https://doi.org/10.1109/tgrs.2017.2730228
2. Anvari R, Mohammadi M, Kahoo AR (2019) Enhancing 3-D seismic data using the t-SVD and optimal shrinkage of singular value. IEEE J Sel Top Appl Earth Obs Remote Sens 12(1):382–388. https://doi.org/10.1109/jstars.2018.2883404
3. Bonar D, Sacchi M (2012) Denoising seismic data using the nonlocal means algorithm. Geophysics 77(1):A5–A8
4. Crummett WP (1986) Seismic exploration. Phys Teach 24(8):462. https://doi.org/10.1119/1.2342095
5. Daubechies I, Lu J, Wu H (2011) Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool. Appl Comput Harmon Anal 30(2):243–261. https://doi.org/10.1016/j.acha.2010.08.002
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