Abstract
Edge detection is a useful tool in the interpretation of potential field data, and the existing edge detection filters are almost functions of first-order horizontal and vertical derivatives. We propose step-edge detection filters to improve the resolution of edge detection results, which use the functions of different-order derivatives to accomplish the edge detection task. We demonstrate the proposed filters on synthetic potential field data, and the results show that the new methods can recognize the edges of the sources more precisely and clearly. We also discuss the application effect of different step-edge detection filters. Lastly, we apply the proposed filters to real potential field data, and the recognized edges of the stratigraphic markers are more precise and clear.
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Acknowledgments
We acknowledge the assistance of the associate editors and the reviewers in improving the paper, and this work is supported by the National Natural Science Foundation of China (Grant No. 41404089), the State Key Program of National Natural Science of China (Grant No. 41430322) and the China Postdoctoral Science Foundation (Grant No. 2014M550173).
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Ma, G., Huang, D. & Liu, C. Step-Edge Detection Filters for the Interpretation of Potential Field Data. Pure Appl. Geophys. 173, 795–803 (2016). https://doi.org/10.1007/s00024-015-1053-6
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DOI: https://doi.org/10.1007/s00024-015-1053-6