Edge detection in the potentialfi eld using the correlation coeffi cients of multidirectional standard deviations

Most edge-detection methods rely on calculating gradient derivatives of the potential field, a process that is easily affected by noise and is therefore of low stability. We propose a new edge-detection method named correlation coeffi cient of multidirectional standard deviations (CCMS) that is sole...

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Bibliographic Details
Published in:应用地球物理（英文版） 2015 (1), p.23-34
Main Authors: Xu Meng-Long, Yang Chang-Bao, Wu Yan-Gang, Chen Jing-Yi, Huan Heng-Fei
Format: Article
Language:English
Online Access:Get full text
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Summary:Most edge-detection methods rely on calculating gradient derivatives of the potential field, a process that is easily affected by noise and is therefore of low stability. We propose a new edge-detection method named correlation coeffi cient of multidirectional standard deviations (CCMS) that is solely based on statistics. First, we prove the reliability of the proposed method using a single model and then a combination of models. The proposed method is evaluated by comparing the results with those obtained by other edge-detection methods. The CCMS method offers outstanding recognition, retains the sharpness of details, and has low sensitivity to noise. We also applied the CCMS method to Bouguer anomaly data of a potash deposit in Laos. The applicability of the CCMS method is shown by comparing the inferred tectonic framework to that inferred from remote sensing (RS) data.
ISSN:1672-7975
1993-0658
DOI:10.1007/s11770-014-0473-5