NAV-Edge: Edge detection of potential-field sources using normalized anisotropy variance
NAV-Edge: Edge detection of potential-field sources using normalized anisotropy variance
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DOI：
10.1190/geo2013-0218.1
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发表时间：
2014-04
期刊：
影响因子：
3.3
通讯作者：
Henglei Zhang;D. Ravat;Y. Marangoni;Xiangyun Hu
中科院分区：
文献类型：
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作者：
Henglei Zhang;D. Ravat;Y. Marangoni;Xiangyun Hu
摘要现有的边缘检测算法大多是基于位场数据的导数，因此，增强了高波数信息，对噪声敏感。基于归一化标准差（NSTD）的思想，提出了位场异常源边缘检测的归一化各向异性方差法（NAV-Edge）。对平衡的、加窗的归一化方差方法的主要改进（即，用于类似目的的NSTD）是应用各向异性高斯函数，该各向异性高斯函数被设计用于检测方向边缘并降低对噪声的敏感性。NAV-Edge不直接使用高阶导数，对噪声的敏感性低于在计算中使用导数的传统方法。利用合成位场数据和真实的磁测数据证明了NAV-Edge的实用性。与现有的几种方法（即，水平梯度振幅的曲率、倾斜角及其总水平导数、θ图和NSTD）.
ABSTRACTMost existing edge-detection algorithms are based on the derivatives of potential-field data, and thus, enhance high wavenumber information and are sensitive to noise. The normalized anisotropy variance method (NAV-Edge) was proposed for detecting edges of potential-field anomaly sources based on the idea of normalized standard deviation (NSTD). The main improvement over the balanced, windowed normalized variance method (i.e., NSTD) used for similar purposes was the application of an anisotropic Gaussian function designed to detect directional edges and reduce sensitivity to noise. NAV-Edge did not directly use higher-order derivatives and was less sensitive to noise than the traditional methods that use derivatives in their calculation. The utility of NAV-Edge was demonstrated using synthetic potential-field data and real magnetic data. Compared with several existing methods (i.e., the curvature of horizontal gradient amplitude, tilt angle and its total-horizontal derivative, theta map, and NSTD)...