Abstract
Enhancement on the edges of the causative source is an indispensable tool in the interpretation of potential-field data. There are a number of methods for recognizing the edges, most of which involve high-pass filters based on derivatives of potential-field data. A new edge-detection method is presented, called the enhanced mathematical morphology (EMM) filter. The EMM filter uses the ratio of the erosion of the total horizontal derivative to the dilation of total horizontal derivative to recognize the edges of the sources, and can display the edges of the shallow and deep bodies simultaneously. The EMM filter does not require the computation of vertical derivatives, which makes this method computationally stable. The EMM filter is tested on synthetic and real potential field data in China. Compared to other edge-detection filters, the new method is able to recognize the source edges more clearly, and the outputs are more insensitive to noise.
References
Beant, K., Gurdeep M., Palak, G., Jasleen, K. (2011), Mathematical Morphological Edge Detection for Different Applications: A Comparative Study, International Journal of Computer Science and Technology 2, 216–220.
Cooper, G.R.J., and Cowan, D.R., (2006), Enhancing potential field data using filters based on the local phase, Computers & Geosciences 32, 1585–1591.
Cooper, G.R.J., and Cowan, D.R., (2008), Edge enhancement of potential-field data using normalized statistics, Geophysics 73, H1–H4.
Gil J. and Kimmel R. (2002) Efficient Dilation, Erosion, Opening, and Closing Algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 1606–1617.
Guo J F, Chen G L. (2008), Analysis of selection of structural element in mathematical morphology with application to infrared point target detection. SPIE 6835, 68350P.
Miller, H. G., and Singh V., (1994), Potential field tilt—A new concept for location of potential field sources, Journal of Applied Geophysics 32, 213–217.
Ramkumar P.B and Pramod K.V (2010), Convex Geometry and Mathematical Morphology in a Generalized Structure, International Journal of Computer Applications 6, 1–6.
Serra, J., (1983), Image Analysis and Mathematical Morphology, Academic Press.
Verduzco, B., Fairhead, J. D., Green, C. M., and Mackenzie, C., (2004), The meter reader—New insights into magnetic derivatives for structural mapping, The Leading Edge 23, 116–119.
Wijns, C., Pere, C., and Kowalczyk, P., (2005), Theta map: Edge detection in magnetic data, Geophysics 70, L39–L43.
Acknowledgments
This work was financially supported by the Deep Exploration Technology and Experimentation project (SinoProbe-09-01). We express our sincere gratitude to Prof. Danian Huang of Jilin University for his dedicated help. Two reviewers contributed valuable critiques of the original manuscript.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, L., Ma, G. & Du, X. Edge Detection in Potential-Field Data by Enhanced Mathematical Morphology Filter. Pure Appl. Geophys. 170, 645–653 (2013). https://doi.org/10.1007/s00024-012-0545-x
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00024-012-0545-x