各向异性滤波算法在地震曲率属性中的应用
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摘要
在曲率属性计算之前需要对图像进行去噪预处理,传统的图像滤波方法在去除噪声的同时会破坏边缘、线条、纹理等图像特征,而基于偏微分方程的P-M模型在平滑过程中会出现块效应。针对这些问题,提出了一种基于张量扩散的各向异性滤波的预处理方法。通过定义散布矩阵来获得丰富的图像局部结构信息,然后利用这些结构来控制扩散过程,以便实现图像的更好滤波。理论分析和实验结果表明,相较于一些常规的图像滤波算法,各向异性滤波得到的曲率属性效果更清晰、质量更高。
It is necessary to have denoising pretreatment for images before the calculation of curvature attribute.However,when eliminating noise,conventional methods of image filtering would meanwhile smear the image features such as edges,lines and textures;while the P-M model based on partial differential equations would lead to blocking effects in the smoothing process.In order to solve these problems,this paper proposed an anisotropic filtering pretreatment based on tensor diffusion,which would get abundant information about the local structure of an image by defining the scatter matrix,and then used these structures to control the diffusion process so as to achieve better image filtering.The theoretical analysis and experimental results show that compare to several general algorithms of image filtering,anisotropic filtering can make the result of curvature attribute clearer and higher in quality.
It is necessary to have denoising pretreatment for images before the calculation of curvature attribute.However,when eliminating noise,conventional methods of image filtering would meanwhile smear the image features such as edges,lines and textures;while the P-M model based on partial differential equations would lead to blocking effects in the smoothing process.In order to solve these problems,this paper proposed an anisotropic filtering pretreatment based on tensor diffusion,which would get abundant information about the local structure of an image by defining the scatter matrix,and then used these structures to control the diffusion process so as to achieve better image filtering.The theoretical analysis and experimental results show that compare to several general algorithms of image filtering,anisotropic filtering can make the result of curvature attribute clearer and higher in quality.
引文
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[9]杨威,霍振华,陈学华.结构方位滤波在体曲率属性中的应用[J].石油物探,2011,50(1):27-32.
[10]WEICKERT J.Partial differential equations in image processing andcomputer vision[D].Mannheim:University of Mannheim,2001.
[11]WEICKERT J,SCHARR H.A scheme for coherence-enchancing dif-fusion filtering with optimized rotation invariance[J].Journal of Vi-sual Communication and Image Representation,2002,13(2):103-118.
[2]张军华,王伟,谭明友,等.曲率属性及其在构造解释中的应用[J].油气地球物理,2009,7(2):1-7.
[3]伍鹏,贺振华,陈学华,等.二维高斯迭代平滑滤波曲率属性及其应用[J].地球物理学进展,2010,25(6):2144-2149.
[4]刘财,李红星,陶春辉,等.模糊嵌套多级中值滤波方法及其在地震数据处理中的应用[J].地球物理学报,2007,50(5):1534-1542.
[5]张亶,陈刚.基于偏微分方程的图像处理[M].北京:高等教育出版社,2004.
[6]唐娅琴.几种图像平滑去噪方法的比较[J].西南大学学报,2009,31(11):125-128.
[7]PERONA P,MALIK J.Scale-space and edge detection using aniso-tropic diffusion[J].IEEE Trans on Pattern Analysis and MachineIntelligence,1990,12(7):629-639.
[8]谢进.偏微分方程(PDEs)在图像去噪中的运用[EB/OL].[2008-04-21].http://www.paper.edu.cn/index.php/default/releasepa-per/content/200804-762.
[9]杨威,霍振华,陈学华.结构方位滤波在体曲率属性中的应用[J].石油物探,2011,50(1):27-32.
[10]WEICKERT J.Partial differential equations in image processing andcomputer vision[D].Mannheim:University of Mannheim,2001.
[11]WEICKERT J,SCHARR H.A scheme for coherence-enchancing dif-fusion filtering with optimized rotation invariance[J].Journal of Vi-sual Communication and Image Representation,2002,13(2):103-118.
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