Seismic noise suppression using weighted nuclear norm minimization method
The weighted nuclear norm minimization method as an extension of nuclear-norm minimization was applied to image denoising originally. It is a kind of low rank matrix approximation method that can estimate the noiseless matrix from its noise version. The effective structures of image have a certain d...
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| Vydáno v: | Journal of applied geophysics Ročník 146; s. 214 - 220 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
01.11.2017
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| ISSN: | 0926-9851, 1879-1859 |
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| Abstract | The weighted nuclear norm minimization method as an extension of nuclear-norm minimization was applied to image denoising originally. It is a kind of low rank matrix approximation method that can estimate the noiseless matrix from its noise version. The effective structures of image have a certain degree of repeatability and the weighted nuclear norm minimization method just utilizes this property to construct an approximate low rank matrix. Taking into account the spatial characteristics of seismic data and the redundancies of valid information, we propose to adopt the weighted nuclear norm minimization method to suppress seismic random noise. In this method the block matching algorithm is helpful for the recovery of seismic events because the texture blocks sharing the same reflection events are the most similar. Even when the signal to noise ratio is −10dB, this novel method still be able to clearly recover signals. Experiments on both synthetic and real seismic data show that the weighted nuclear norm minimization method can not only suppress the random noise but also better preserves the valid information of seismic signal when compared to the common seismic denoising methods such as the Wavelet and Time Frequency Peak Filter. |
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| AbstractList | The weighted nuclear norm minimization method as an extension of nuclear-norm minimization was applied to image denoising originally. It is a kind of low rank matrix approximation method that can estimate the noiseless matrix from its noise version. The effective structures of image have a certain degree of repeatability and the weighted nuclear norm minimization method just utilizes this property to construct an approximate low rank matrix. Taking into account the spatial characteristics of seismic data and the redundancies of valid information, we propose to adopt the weighted nuclear norm minimization method to suppress seismic random noise. In this method the block matching algorithm is helpful for the recovery of seismic events because the texture blocks sharing the same reflection events are the most similar. Even when the signal to noise ratio is −10dB, this novel method still be able to clearly recover signals. Experiments on both synthetic and real seismic data show that the weighted nuclear norm minimization method can not only suppress the random noise but also better preserves the valid information of seismic signal when compared to the common seismic denoising methods such as the Wavelet and Time Frequency Peak Filter. |
| Author | Qian, Zhihong Li, Juan Li, Yue Wang, Daixiang Ji, Shuo |
| Author_xml | – sequence: 1 givenname: Juan surname: Li fullname: Li, Juan email: ljuan@jlu.edu.cn – sequence: 2 givenname: Daixiang surname: Wang fullname: Wang, Daixiang – sequence: 3 givenname: Shuo surname: Ji fullname: Ji, Shuo – sequence: 4 givenname: Yue surname: Li fullname: Li, Yue – sequence: 5 givenname: Zhihong surname: Qian fullname: Qian, Zhihong |
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| Cites_doi | 10.1080/09500340.2015.1068392 10.1190/1.3552706 10.1002/ima.22145 10.1190/1.1439700 10.1155/2015/979415 10.1016/j.camwa.2013.08.034 10.1016/j.jappgeo.2014.07.012 10.1190/geo2011-0235.1 10.1016/j.tecto.2010.07.017 10.1007/s11770-013-0362-8 10.1109/78.651165 10.1190/1.1443920 10.1016/j.jappgeo.2014.03.009 10.1190/geo2014-0116.1 10.1109/TGRS.2013.2282422 10.1137/080738970 10.1109/TIP.2016.2571062 10.1016/j.physa.2011.04.009 10.1016/j.jappgeo.2014.09.011 |
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| References | Gaci (bb0045) 2014; 52 Damber, Kaamran, Vasudevan (bb0040) 2015; 62 Liu, Lin (bb0065) 2010; vol. 1 Russell, Hampson, Chun (bb0095) 1990; 9 Gu, Zhang, Zuo (bb0055) 2014 Shang (bb0105) 2013; 10 Abma, Claerbout (bb0005) 1995; 60 Gorszczyk, Adamczyk, Michal (bb0050) 2014; 105 Chao, Yue (bb0020) 2013; 347 Kumar, Oueity, Clowes, Herrmann (bb0060) 2011; 508 Oliveira, Henriques, Leite (bb0075) 2012; 391 Zhai (bb0125) 2014; 109 Bonar, Sacchi (bb0010) 2012; 77 Wang, Zhang, L. (bb0115) 2012 Cui, Zhang, Wang, Zhang (bb0035) 2015; 2015 Chen, Zhou, Yuan, Jin (bb0030) 2014; 23 Wang, Ren, Wang (bb0120) 2013; 66 Qu, Cao, Zhu, Ren (bb0085) 2011; 32 Liu, Zhang, Li, Zhao, Li (bb0070) 2015; 25 Cai, Cand'es, Shen (bb0015) 2010; 20 Oropeza, Sacchi (bb0080) 2011; 76 Ren (bb0090) 2016; 25 Sacchi, Ulryth, Walker (bb0100) 1998; 46 Chen, Sacchi (bb0025) 2015; 80 Wang, Gao (bb0110) 2014; 110 Chen (10.1016/j.jappgeo.2017.09.013_bb0025) 2015; 80 Shang (10.1016/j.jappgeo.2017.09.013_bb0105) 2013; 10 Oropeza (10.1016/j.jappgeo.2017.09.013_bb0080) 2011; 76 Zhai (10.1016/j.jappgeo.2017.09.013_bb0125) 2014; 109 Wang (10.1016/j.jappgeo.2017.09.013_bb0120) 2013; 66 Liu (10.1016/j.jappgeo.2017.09.013_bb0065) 2010; vol. 1 Gorszczyk (10.1016/j.jappgeo.2017.09.013_bb0050) 2014; 105 Sacchi (10.1016/j.jappgeo.2017.09.013_bb0100) 1998; 46 Cui (10.1016/j.jappgeo.2017.09.013_bb0035) 2015; 2015 Damber (10.1016/j.jappgeo.2017.09.013_bb0040) 2015; 62 Cai (10.1016/j.jappgeo.2017.09.013_bb0015) 2010; 20 Chen (10.1016/j.jappgeo.2017.09.013_bb0030) 2014; 23 Wang (10.1016/j.jappgeo.2017.09.013_bb0115) 2012 Bonar (10.1016/j.jappgeo.2017.09.013_bb0010) 2012; 77 Chao (10.1016/j.jappgeo.2017.09.013_bb0020) 2013; 347 Kumar (10.1016/j.jappgeo.2017.09.013_bb0060) 2011; 508 Gaci (10.1016/j.jappgeo.2017.09.013_bb0045) 2014; 52 Ren (10.1016/j.jappgeo.2017.09.013_bb0090) 2016; 25 Wang (10.1016/j.jappgeo.2017.09.013_bb0110) 2014; 110 Qu (10.1016/j.jappgeo.2017.09.013_bb0085) 2011; 32 Abma (10.1016/j.jappgeo.2017.09.013_bb0005) 1995; 60 Liu (10.1016/j.jappgeo.2017.09.013_bb0070) 2015; 25 Oliveira (10.1016/j.jappgeo.2017.09.013_bb0075) 2012; 391 Russell (10.1016/j.jappgeo.2017.09.013_bb0095) 1990; 9 Gu (10.1016/j.jappgeo.2017.09.013_bb0055) 2014 |
| References_xml | – volume: 62 start-page: 1856 year: 2015 end-page: 1864 ident: bb0040 article-title: Reduction of speckle noise from optical coherence tomography image using multi-frame weighted nuclear norm minimization method publication-title: J. Mod. Opt. – volume: 20 start-page: 1956 year: 2010 end-page: 1982 ident: bb0015 article-title: A singular value thresholding algorithm for matrix completion publication-title: SIAM J. Optim. – volume: 66 start-page: 1729 year: 2013 end-page: 1742 ident: bb0120 article-title: Anisotropic second and fourth order diffusion models based on convolutional virtual electric field for image denoising publication-title: Comput. Math. Appl. – volume: 80 start-page: V1 year: 2015 end-page: V11 ident: bb0025 article-title: Robust reduced-rank filtering for erratic seismic noise attenuation publication-title: Geophysics – start-page: 2862 year: 2014 end-page: 2869 ident: bb0055 publication-title: Weighted nuclear norm minimization with application to image denoising [C] – volume: 76 start-page: V25 year: 2011 end-page: V32 ident: bb0080 article-title: Simultaneous seismic data denoising and reconstruction via multichannel singular spectrum analysis publication-title: Geophysics – volume: 46 start-page: 31 year: 1998 end-page: 38 ident: bb0100 article-title: Interpolation and extrapolation using a high-resolution discrete Fourier transform publication-title: IEEE Trans. Signal Process. – volume: 25 start-page: 3426 year: 2016 end-page: 3437 ident: bb0090 article-title: Image deblurring via enhanced low rank prior publication-title: IEEE Trans. Image Process. – volume: 2015 year: 2015 ident: bb0035 article-title: Weighted nuclear norm minimization based tongue specular reflection removal publication-title: Math. Probl. Eng. – volume: 110 start-page: 135 year: 2014 end-page: 143 ident: bb0110 article-title: A new method for random noise attenuation in seismic data based on anisotropic fractional-grandient operatous publication-title: J. Appl. Geophys. – volume: 109 start-page: 62 year: 2014 end-page: 70 ident: bb0125 article-title: Seismic data denoising based on the fractional Fourier transformation publication-title: J. Appl. Geophys. – volume: 32 start-page: 815 year: 2011 end-page: 819 ident: bb0085 article-title: An improved total variation technique for seismic image denoising publication-title: Acta Petrol. Sin. – volume: 9 start-page: 31 year: 1990 end-page: 37 ident: bb0095 article-title: Noise elimination and the radon transform, Part2[J] publication-title: Lead. Edge – volume: 52 start-page: 4558 year: 2014 end-page: 4563 ident: bb0045 article-title: The use of wavelet-based denoising techniques to enhance the first-arrival picking on seismic traces publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 391 start-page: 106 year: 2012 end-page: 110 ident: bb0075 article-title: Seismic denoising using curvelet analysis publication-title: Physica A – volume: 10 start-page: 30 year: 2013 end-page: 40 ident: bb0105 article-title: Seismic random noise suppression using an adaptive nonlocal means algorithm publication-title: Appl. Geophys. – volume: 25 start-page: 310 year: 2015 end-page: 316 ident: bb0070 article-title: Medical image fusion based on nuclear norm minimization publication-title: Int. J. Imaging Syst. Technol. – volume: 347 start-page: 2 year: 2013 end-page: 12 ident: bb0020 article-title: Seismic random noise attenuation and signal-preserving by multiple directional time-frequency peak filtering publication-title: Compt. Rendus Geosci. – volume: vol. 1 year: 2010 ident: bb0065 article-title: Learning PDEs for image restoration via optimal control publication-title: ECCV – volume: 508 start-page: 106 year: 2011 end-page: 116 ident: bb0060 article-title: Enhancing crustal reflection data through curvelet denoising publication-title: Tectonophysics – year: 2012 ident: bb0115 article-title: Nonlocal spectral prior model for low-level vision publication-title: ACCV – volume: 60 start-page: 1887 year: 1995 end-page: 1896 ident: bb0005 article-title: Lateral prediction for noise attenuation by t-x and f-x techniques publication-title: Geophysics – volume: 77 year: 2012 ident: bb0010 article-title: Denoising seismic data using the nonlocal means algorithm publication-title: Geophysics – volume: 105 start-page: 78 year: 2014 end-page: 94 ident: bb0050 article-title: Application of curvelet denoising to 2D and 3D seismic data — practical considerations publication-title: J. Appl. Geophys. – volume: 23 start-page: 481 year: 2014 end-page: 495 ident: bb0030 article-title: Application of empirical mode decomposition to random noise attenuation of seismic data publication-title: J. Seism. Explor. – volume: 62 start-page: 1856 issue: 21 year: 2015 ident: 10.1016/j.jappgeo.2017.09.013_bb0040 article-title: Reduction of speckle noise from optical coherence tomography image using multi-frame weighted nuclear norm minimization method publication-title: J. Mod. Opt. doi: 10.1080/09500340.2015.1068392 – volume: 76 start-page: V25 issue: 3 year: 2011 ident: 10.1016/j.jappgeo.2017.09.013_bb0080 article-title: Simultaneous seismic data denoising and reconstruction via multichannel singular spectrum analysis publication-title: Geophysics doi: 10.1190/1.3552706 – volume: 25 start-page: 310 issue: 4 year: 2015 ident: 10.1016/j.jappgeo.2017.09.013_bb0070 article-title: Medical image fusion based on nuclear norm minimization publication-title: Int. J. Imaging Syst. Technol. doi: 10.1002/ima.22145 – volume: 9 start-page: 31 issue: 11 year: 1990 ident: 10.1016/j.jappgeo.2017.09.013_bb0095 article-title: Noise elimination and the radon transform, Part2[J] publication-title: Lead. Edge doi: 10.1190/1.1439700 – year: 2012 ident: 10.1016/j.jappgeo.2017.09.013_bb0115 article-title: Nonlocal spectral prior model for low-level vision – volume: 2015 year: 2015 ident: 10.1016/j.jappgeo.2017.09.013_bb0035 article-title: Weighted nuclear norm minimization based tongue specular reflection removal publication-title: Math. Probl. Eng. doi: 10.1155/2015/979415 – volume: 66 start-page: 1729 issue: 10 year: 2013 ident: 10.1016/j.jappgeo.2017.09.013_bb0120 article-title: Anisotropic second and fourth order diffusion models based on convolutional virtual electric field for image denoising publication-title: Comput. Math. Appl. doi: 10.1016/j.camwa.2013.08.034 – volume: 109 start-page: 62 issue: 109 year: 2014 ident: 10.1016/j.jappgeo.2017.09.013_bb0125 article-title: Seismic data denoising based on the fractional Fourier transformation publication-title: J. Appl. Geophys. doi: 10.1016/j.jappgeo.2014.07.012 – volume: 77 issue: 1 year: 2012 ident: 10.1016/j.jappgeo.2017.09.013_bb0010 article-title: Denoising seismic data using the nonlocal means algorithm publication-title: Geophysics doi: 10.1190/geo2011-0235.1 – volume: 508 start-page: 106 issue: 1–4 year: 2011 ident: 10.1016/j.jappgeo.2017.09.013_bb0060 article-title: Enhancing crustal reflection data through curvelet denoising publication-title: Tectonophysics doi: 10.1016/j.tecto.2010.07.017 – volume: 10 start-page: 30 issue: 1 year: 2013 ident: 10.1016/j.jappgeo.2017.09.013_bb0105 article-title: Seismic random noise suppression using an adaptive nonlocal means algorithm publication-title: Appl. Geophys. doi: 10.1007/s11770-013-0362-8 – volume: 46 start-page: 31 issue: 1–3 year: 1998 ident: 10.1016/j.jappgeo.2017.09.013_bb0100 article-title: Interpolation and extrapolation using a high-resolution discrete Fourier transform publication-title: IEEE Trans. Signal Process. doi: 10.1109/78.651165 – volume: 60 start-page: 1887 issue: 6 year: 1995 ident: 10.1016/j.jappgeo.2017.09.013_bb0005 article-title: Lateral prediction for noise attenuation by t-x and f-x techniques publication-title: Geophysics doi: 10.1190/1.1443920 – volume: 105 start-page: 78 year: 2014 ident: 10.1016/j.jappgeo.2017.09.013_bb0050 article-title: Application of curvelet denoising to 2D and 3D seismic data — practical considerations publication-title: J. Appl. Geophys. doi: 10.1016/j.jappgeo.2014.03.009 – volume: 80 start-page: V1 issue: 1 year: 2015 ident: 10.1016/j.jappgeo.2017.09.013_bb0025 article-title: Robust reduced-rank filtering for erratic seismic noise attenuation publication-title: Geophysics doi: 10.1190/geo2014-0116.1 – volume: 52 start-page: 4558 issue: 8 year: 2014 ident: 10.1016/j.jappgeo.2017.09.013_bb0045 article-title: The use of wavelet-based denoising techniques to enhance the first-arrival picking on seismic traces publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2013.2282422 – volume: 20 start-page: 1956 issue: 4 year: 2010 ident: 10.1016/j.jappgeo.2017.09.013_bb0015 article-title: A singular value thresholding algorithm for matrix completion publication-title: SIAM J. Optim. doi: 10.1137/080738970 – volume: vol. 1 year: 2010 ident: 10.1016/j.jappgeo.2017.09.013_bb0065 article-title: Learning PDEs for image restoration via optimal control – volume: 32 start-page: 815 issue: 5 year: 2011 ident: 10.1016/j.jappgeo.2017.09.013_bb0085 article-title: An improved total variation technique for seismic image denoising publication-title: Acta Petrol. Sin. – volume: 347 start-page: 2 issue: 1 year: 2013 ident: 10.1016/j.jappgeo.2017.09.013_bb0020 article-title: Seismic random noise attenuation and signal-preserving by multiple directional time-frequency peak filtering publication-title: Compt. Rendus Geosci. – start-page: 2862 year: 2014 ident: 10.1016/j.jappgeo.2017.09.013_bb0055 – volume: 25 start-page: 3426 issue: 7 year: 2016 ident: 10.1016/j.jappgeo.2017.09.013_bb0090 article-title: Image deblurring via enhanced low rank prior publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2016.2571062 – volume: 391 start-page: 106 issue: 5 year: 2012 ident: 10.1016/j.jappgeo.2017.09.013_bb0075 article-title: Seismic denoising using curvelet analysis publication-title: Physica A doi: 10.1016/j.physa.2011.04.009 – volume: 23 start-page: 481 issue: 6 year: 2014 ident: 10.1016/j.jappgeo.2017.09.013_bb0030 article-title: Application of empirical mode decomposition to random noise attenuation of seismic data publication-title: J. Seism. Explor. – volume: 110 start-page: 135 year: 2014 ident: 10.1016/j.jappgeo.2017.09.013_bb0110 article-title: A new method for random noise attenuation in seismic data based on anisotropic fractional-grandient operatous publication-title: J. Appl. Geophys. doi: 10.1016/j.jappgeo.2014.09.011 |
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