Random noise attenuation in seismic data using Hankel sparse low-rank approximation

[1]  Wei Chen,et al.  An open-source Matlab code package for improved rank-reduction 3D seismic data denoising and reconstruction , 2016, Comput. Geosci..

[2]  Min Bai,et al.  Substituting smoothing with low-rank decomposition — Applications to least-squares reverse time migration of simultaneous source and incomplete seismic data , 2019, GEOPHYSICS.

[3]  Yangkang Chen,et al.  Double Sparsity Dictionary for Seismic Noise Attenuation , 2016 .

[4]  Yatong Zhou,et al.  Empirical Low-Rank Approximation for Seismic Noise Attenuation , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Ivan W. Selesnick,et al.  Sparse Regularization via Convex Analysis , 2017, IEEE Transactions on Signal Processing.

[6]  Mauricio D. Sacchi,et al.  Denoising seismic data using the nonlocal means algorithm , 2012 .

[7]  Rick Chartrand,et al.  Compressed sensing recovery via nonconvex shrinkage penalties , 2015, ArXiv.

[8]  Patrick L. Combettes,et al.  Perspective Functions: Properties, Constructions, and Examples , 2016, Set-Valued and Variational Analysis.

[9]  Bin Liu,et al.  Structural complexity‐guided predictive filtering , 2020, Geophysical Prospecting.

[10]  Yangkang Chen,et al.  Dip-separated structural filtering using seislet transform and adaptive empirical mode decomposition based dip filter , 2016 .

[11]  Ilker Bayram On the Convergence of the Iterative Shrinkage/Thresholding Algorithm With a Weakly Convex Penalty , 2016, IEEE Trans. Signal Process..

[12]  Yangkang Chen,et al.  Simultaneous denoising and interpolation of 2D seismic data using data-driven non-negative dictionary learning , 2017, Signal Process..

[13]  Ali Gholami,et al.  Seismic random noise attenuation via 3D block matching , 2017 .

[14]  Jingwei Hu,et al.  Iterative deblending of simultaneous-source seismic data using seislet-domain shaping regularization , 2014 .

[15]  Shaohuan Zu,et al.  The Interpolation of Sparse Geophysical Data , 2018, Surveys in Geophysics.

[16]  A. Bruce,et al.  WAVESHRINK WITH FIRM SHRINKAGE , 1997 .

[17]  Breno Bahia,et al.  Robust singular spectrum analysis via the bifactored gradient descent algorithm , 2019 .

[18]  Yangkang Chen,et al.  Non-stationary least-squares complex decomposition for microseismic noise attenuation , 2018 .

[19]  Yangkang Chen,et al.  Random noise attenuation using local signal-and-noise orthogonalization , 2015 .

[20]  R. Vautard,et al.  Singular-spectrum analysis: a toolkit for short, noisy chaotic signals , 1992 .

[21]  Yangkang Chen,et al.  Least-Squares Gaussian Beam Transform for Seismic Noise Attenuation , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Yangkang Chen,et al.  Seismic Random Noise Attenuation Using Sparse Low-Rank Estimation of the Signal in the Time–Frequency Domain , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[23]  Nabeel Ali Khan,et al.  Random noise attenuation of 2D seismic data based on sparse low-rank estimation of the seismic signal , 2020, Comput. Geosci..

[24]  Yangkang Chen,et al.  Random noise attenuation by f-x empirical mode decomposition predictive filtering , 2014 .

[25]  Yangkang Chen,et al.  Fast dictionary learning for noise attenuation of multidimensional seismic data , 2017, Geophysical Journal International.

[26]  Mauricio D. Sacchi,et al.  Multidimensional de-aliased Cadzow reconstruction of seismic records , 2013 .

[27]  Jinkun Cheng,et al.  Computational efficient multidimensional singular spectrum analysis for prestack seismic data reconstruction , 2019, GEOPHYSICS.

[28]  Amin Roshandel Kahoo,et al.  Application of the local maximum synchrosqueezing transform for seismic data , 2021, Digit. Signal Process..

[29]  Yangkang Chen,et al.  EMD-seislet transform , 2018 .

[30]  Yangkang Chen,et al.  Relative time seislet transform , 2020 .

[31]  Shuaiqi Liu,et al.  Hankel Low-Rank Approximation for Seismic Noise Attenuation , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Yongjun Zhang,et al.  Large-Scale Remote Sensing Image Retrieval by Deep Hashing Neural Networks , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[33]  Yangkang Chen,et al.  Unsupervised Seismic Random Noise Attenuation Based on Deep Convolutional Neural Network , 2019, IEEE Access.

[34]  Siwei Yu,et al.  Complex Variational Mode Decomposition for Slop-Preserving Denoising , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[35]  Mokhtar Mohammadi,et al.  Seismic Random Noise Attenuation Using Synchrosqueezed Wavelet Transform and Low-Rank Signal Matrix Approximation , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[36]  Yangkang Chen,et al.  Application of spectral decomposition using regularized non-stationary autoregression to random noise attenuation , 2015 .

[37]  Yangkang Chen,et al.  Robust damped rank-reduction method for simultaneous denoising and reconstruction of 5D seismic data , 2021 .

[38]  Yangkang Chen,et al.  De‐aliased and de‐noise Cadzow filtering for seismic data reconstruction , 2019, Geophysical Prospecting.

[39]  Mauricio D. Sacchi,et al.  Robust tensor-completion algorithm for 5D seismic-data reconstruction , 2019, GEOPHYSICS.

[40]  Wei Liu,et al.  An effective approach to attenuate random noise based on compressive sensing and curvelet transform , 2016 .

[41]  Min Bai,et al.  Five-dimensional seismic data reconstruction using the optimally damped rank-reduction method , 2019, Geophysical Journal International.

[42]  Breno Bahia,et al.  Vector-valued seismic data denoising via widely-linear autoregressive models , 2019 .

[43]  Baojun Yang,et al.  Statistical properties of the random noise in seismic data , 2015 .

[44]  Weilin Huang,et al.  Simultaneous denoising and reconstruction of 5-D seismic data via damped rank-reduction method , 2016 .

[45]  Qiang Zhao,et al.  Iterative Double Laplacian-Scaled Low-Rank Optimization for Under-Sampled and Noisy Signal Recovery , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[46]  Steve McLaughlin,et al.  Development of EMD-Based Denoising Methods Inspired by Wavelet Thresholding , 2009, IEEE Transactions on Signal Processing.