基于方向模板的保持边缘平滑后地震图像的不连续性检测(英文)
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摘要
鉴于地震数据不连续性检测的重要性,本文提出了一种保持和检测地震图像不连续性(如:岩层,断层,河道等)的方法.通常在图象不连续的地方,象素值会有较大的差异,文中用4×4的方向模板计算目标点周围六个方向上的差值,当最大差值超过某个门限值时,则可认为该点为不连续点,由此来检测地震图像的不连续性.由于包含重要信息的区域受噪声的影响通常比其他地方严重,而且基于差值的不连续性检测算法对噪声较为敏感,所以在不连续性检测之前降低地震图像的噪声是很重要的.普通的平滑去噪方法会造成边缘模糊,不利于不连续性检测.本文采用旋转模板的非线性平滑方法,用四个六边形和一个八边形模板在目标像素周围旋转,用与目标像素标准差最小(最同类)的模板内那些点的均值代替目标像素的值,从而实现对地震图象的保边缘平滑去噪处理.理论模型和实际数据处理结果表明:与Y.Luo等人提出的保边缘平滑方法相比,本文的保边缘平滑处理方法提高了计算效率和峰值信噪比;将文中提出的保边缘平滑方法和基于方向模板的不连续性检测方法结合使用,得到的不连续性检测结果比直接检测更清晰.地震数据解释人员可根据检测到的不连续性来识别断层、岩层、河道等.
Due to the importance of detecting discontinuities in seismic data,this paper proposes alternative methods for preserving and detecting discontinuities(i.e.horizons,faults,channels etc.) in seismic image.Discontinuities in seismic data usually indicate the sudden change in intensity or amplitude.In this paper the 4×4 masks with six directions are proposed to detect discontinuities.An edge pixel usually belongs to one of the six possible edge directions.The shaded pixels in directional masks are used to find the difference between pixels.The direction with maximum difference larger than the given threshold is considered as an edge pixel.Areas that contain important information are often noisier than others,and the discontinuity detection algorithms are sensitive to random noise since they are based on difference of data,so suppressing random noise is important before detecting discontinuity.The common smoothing method often blurs the edges of the image that is disadvantageous to edge detection.This paper adopts nonlinear smoothing by using rotating masks,four hexagonal masks and one octagonal mask,the smoothing process replaces the pixel intensity of the most homogeneous mask among the proposed masks.Compared to Luo's edge preserving smoothing(EPS),the results have shown improvements in filter computation time and peak signal to noise ratio during smoothing process,also discontinuity detection with EPS is clearer than without EPS.Seismic data interpreters can use discontinuities detection to identify faults,horizons,channels etc.
Due to the importance of detecting discontinuities in seismic data,this paper proposes alternative methods for preserving and detecting discontinuities(i.e.horizons,faults,channels etc.) in seismic image.Discontinuities in seismic data usually indicate the sudden change in intensity or amplitude.In this paper the 4×4 masks with six directions are proposed to detect discontinuities.An edge pixel usually belongs to one of the six possible edge directions.The shaded pixels in directional masks are used to find the difference between pixels.The direction with maximum difference larger than the given threshold is considered as an edge pixel.Areas that contain important information are often noisier than others,and the discontinuity detection algorithms are sensitive to random noise since they are based on difference of data,so suppressing random noise is important before detecting discontinuity.The common smoothing method often blurs the edges of the image that is disadvantageous to edge detection.This paper adopts nonlinear smoothing by using rotating masks,four hexagonal masks and one octagonal mask,the smoothing process replaces the pixel intensity of the most homogeneous mask among the proposed masks.Compared to Luo's edge preserving smoothing(EPS),the results have shown improvements in filter computation time and peak signal to noise ratio during smoothing process,also discontinuity detection with EPS is clearer than without EPS.Seismic data interpreters can use discontinuities detection to identify faults,horizons,channels etc.
引文
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[11]李红星,刘财,陶春辉.图像边缘检测方法在地震剖面同相轴自动检测中的应用研究[J].地球物理学进展,2007,22(5):1607~1610Li H X,Liu C,Tao C H.The study of application of edgemeasuring technique to the detection of phase axis of the seis-mic section[J].Progress in Geophysics.2007,22(5):1607~1610
[2]Kuwahara M,Hachimura K,Ehiu S,Kinoshita M.Process-ing of RI-angiocardiographic images[A].In:K.Preston,M.Onoe,(Eds.).Digital processing of biomedical images[C].NewYork:Plenum Press,1976,187~203.
[3]Tomita F,Tsuji S.Extraction of multiple regions by smoot-hing in selected neighborhood[J].IEEE Trans.System Manand Cybernetics.1977,107~109.
[4]Nagao M,Matsuyama T.Edge preserving smoothing[C].Computer and graphics and image processing.1979,374~407.
[5]Chitwong S,Cheevasuit F,Dejhan K,Mitatha S,Nokyoo C,Paungma T.Segmentation on edge preserving smoothing im-age based on graph theory[C].Geoscience and Remote Sens-ing Symposium,2000.Proceedings.IGARSS 2000.IEEE2000 International.2000,2:621~623.
[6]王绪松,杨长春.对地震图像进行保边滤波的非线性各向异性扩散算法[J].地球物理学进展,2006,21(2):452~457.Wang X S,Yang C C.An edge-preserving smoothing algo-rithm of seismic image using nonlinear anisotropic diffusion e-quation[J].Progress in geophysics,2006,21(2):452~457.
[7]Cramariuc B,Tabus I,Gabbouj M.Use of predictive codingdistribution for edge detection[C].Proceedings of the IEEEworkshop on nonlinear signal and image processing.1997,342~346.
[8]Kang C C,Wang W J.A novel edge detection method basedon the maximizing objective function[J].Pattern Recognition.2007,40(2):609~618.
[9]Liang L R,Looney C G.Competitive fuzzy edge detection[J].Applied soft computing.2003,3:123~137.
[10]Kim J,Jeon K,Jeong J.H.264 Intra Mode decision for re-ducing complexity using directional masks and neighboringmodes[C].Lecture Notes in Computer Science Lncs 4319.2006,959~968.
[11]李红星,刘财,陶春辉.图像边缘检测方法在地震剖面同相轴自动检测中的应用研究[J].地球物理学进展,2007,22(5):1607~1610Li H X,Liu C,Tao C H.The study of application of edgemeasuring technique to the detection of phase axis of the seis-mic section[J].Progress in Geophysics.2007,22(5):1607~1610
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