自适应非局部均值地震随机噪声压制(英文)
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摘要
非局部均值滤波是一种基于图像信息冗余的去噪方法,其认为图像自身的有效结构具有一定的重复性,而随机噪声则不具备这一特点,通过利用图像本身的自相似性来达到压制随机噪声的目的,是一种全局的去噪方法。本文把这一思想引入地震数据随机噪声压制中,针对传统非局部均值滤波计算量过大的问题,文章采用分块非局部均值的方式来减少计算量;针对滤波参数选取会影响非局部均值滤波效果的问题,提出一种简单的自适应滤波参数地震数据分块非局部均值算法。模型和实际数据处理结果表明:相对于传统的去噪算法(如f-x反褶积),该方法在压制随机噪声的同时对有效信号保护地更好,具有更高的保真度,更有利于后续的处理和解释工作。
Nonlocal means filtering is a noise attenuation method based on redundancies in image information. It is also a nonlocal denoising method that uses the self-similarity of an image, assuming that the valid structures of the image have a certain degree of repeatability that the random noise lacks. In this paper, we use nonlocal means filtering in seismic random noise suppression. To overcome the problems caused by expensive computational costs and improper filter parameters, this paper proposes a block-wise implementation of the nonlocal means method with adaptive filter parameter estimation. Tests with synthetic data and real 2D post-stack seismic data demonstrate that the proposed algorithm better preserves valid seismic information and has a higher accuracy when compared with traditional seismic denoising methods (e.g., f-x deconvolution), which is important for subsequent seismic processing and interpretation.
Nonlocal means filtering is a noise attenuation method based on redundancies in image information. It is also a nonlocal denoising method that uses the self-similarity of an image, assuming that the valid structures of the image have a certain degree of repeatability that the random noise lacks. In this paper, we use nonlocal means filtering in seismic random noise suppression. To overcome the problems caused by expensive computational costs and improper filter parameters, this paper proposes a block-wise implementation of the nonlocal means method with adaptive filter parameter estimation. Tests with synthetic data and real 2D post-stack seismic data demonstrate that the proposed algorithm better preserves valid seismic information and has a higher accuracy when compared with traditional seismic denoising methods (e.g., f-x deconvolution), which is important for subsequent seismic processing and interpretation.
引文
Bednar,J.B.,1983,Applications of median filtering todeconvolution,pulse estimation,and statistical editing ofseismic data: Geophysics,48(12),1598– 1610.
Bonar,D.,and Sacchi,M.,2012,Denoising seismic datausing the nonlocal means algorithm: Geophysics,77(1),A5– A8.
Buades,A.,Coll,B.,and Morel,J.M.,2005,A non-localalgorithm for image denoising: IEEE Computer SocietyConference on Computer Vision and Pattern Recognition,60– 65.
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Buades,A.,Coll,B.,and Morel,J.M.,2008,Image andmovie denoising by nonlocal means: IJCV,76(2),123–139.
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Canales,L.L.,1984,Random noise reduction: 54th Annual International Meeting,SEG,Expanded Abstracts,525–527.
Coupé,P.,Hellier,P.,and Prima,S.,et al.,2008,3Dwavelet subbands mixing for image denoising: Journal ofBiomedical Imaging,2008(3),1– 11.
Coupé,P.,Yger,P.,and Prima,S.,et al.,2008,Anoptimized blockwise nonlocal means denoising filter for3-D magnetic resonance images: IEEE Transactions onMedical Imaging,27(4),425– 441.
Deledalle,C.A.,Denis,L.,and Tupin,F.,2011,Nl-insar:Nonlocal interferogram estimation: IEEE Transactionson Geoscience and Remote Sensing,49(4),1441– 1452.
Efros,A.A.,and Leung,T.K.,1999,Texture synthesis bynon-parametric sampling: ICCV,1033– 1038.
Mahmoudi,M.,and Sapiro,G.,2005,Fast image and videodenoising via nonlocal means of similar neighborhoods:IEEE Signal Processing Letters,12(12),839– 842.
Manjón,J.V.,Coupé,P.,and Bonmatí,M.L.,et al.,2010,Adaptive non-local means denoising of MR imageswith spatially varying noise levels: Journal of MagneticResonance Imaging,31(1),192– 203.
Neelamani,R.,Baumstein,A.I.,and Gillard,D.G.,et al.,2008,Coherent and random noise attenuation using thecurvelet transform: The Leading Edge,27(2),240– 248.
Sheng,B.,Li,P.,and Sun,H.,2009,Image-Based MaterialRestyling with Fast Non-local Means Filtering: ICIG,841– 846.
Stewart,R.R.,and Schieck,D.G.,1993,3-D F-K filtering:Journal of Seismic Exploration,2,41– 54.
Wang,J.,Guo,Y.,and Ying,Y.,et al.,2006,Fast non-local algorithm for image denoising: IEEE InternationalConference on Image Processing,1429– 1432.
Bonar,D.,and Sacchi,M.,2012,Denoising seismic datausing the nonlocal means algorithm: Geophysics,77(1),A5– A8.
Buades,A.,Coll,B.,and Morel,J.M.,2005,A non-localalgorithm for image denoising: IEEE Computer SocietyConference on Computer Vision and Pattern Recognition,60– 65.
Buades,A.,Coll,B.,and Morel,J.M.,2005,A reviewof image denoising algorithms,with a new one: SIAMJournal on Multiscale Modeling and Simulation,4(2),490– 530.
Buades,A.,Coll,B.,and Morel,J.M.,2008,Image andmovie denoising by nonlocal means: IJCV,76(2),123–139.
Buades,A.,Coll,B.,and Morel,J.M.,2010,Imagedenoising methods.A new nonlocal principle: SIAMReview,52(1),113– 147.
Canales,L.L.,1984,Random noise reduction: 54th Annual International Meeting,SEG,Expanded Abstracts,525–527.
Coupé,P.,Hellier,P.,and Prima,S.,et al.,2008,3Dwavelet subbands mixing for image denoising: Journal ofBiomedical Imaging,2008(3),1– 11.
Coupé,P.,Yger,P.,and Prima,S.,et al.,2008,Anoptimized blockwise nonlocal means denoising filter for3-D magnetic resonance images: IEEE Transactions onMedical Imaging,27(4),425– 441.
Deledalle,C.A.,Denis,L.,and Tupin,F.,2011,Nl-insar:Nonlocal interferogram estimation: IEEE Transactionson Geoscience and Remote Sensing,49(4),1441– 1452.
Efros,A.A.,and Leung,T.K.,1999,Texture synthesis bynon-parametric sampling: ICCV,1033– 1038.
Mahmoudi,M.,and Sapiro,G.,2005,Fast image and videodenoising via nonlocal means of similar neighborhoods:IEEE Signal Processing Letters,12(12),839– 842.
Manjón,J.V.,Coupé,P.,and Bonmatí,M.L.,et al.,2010,Adaptive non-local means denoising of MR imageswith spatially varying noise levels: Journal of MagneticResonance Imaging,31(1),192– 203.
Neelamani,R.,Baumstein,A.I.,and Gillard,D.G.,et al.,2008,Coherent and random noise attenuation using thecurvelet transform: The Leading Edge,27(2),240– 248.
Sheng,B.,Li,P.,and Sun,H.,2009,Image-Based MaterialRestyling with Fast Non-local Means Filtering: ICIG,841– 846.
Stewart,R.R.,and Schieck,D.G.,1993,3-D F-K filtering:Journal of Seismic Exploration,2,41– 54.
Wang,J.,Guo,Y.,and Ying,Y.,et al.,2006,Fast non-local algorithm for image denoising: IEEE InternationalConference on Image Processing,1429– 1432.
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