The monogenic signal of potential-field data: A Python implementation

(2017) Marlon C. Hidalgo-Gato, Valéria C. F. Barbosa


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Hidalgo-Gato, M., and V. Barbosa (2017), The monogenic signal of potential-field data: A Python implementation, Geophysics, F9–F14, doi:10.1190/geo2016-0099.1.

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Describes a Python implementation of the methods in Edge detection of potential-field sources using scale-space monogenic signal: Fundamental principles.


We have developed codes to calculate the local amplitude, the local phase, and the local orientation of the nonscale and the Poisson's scale-space monogenic signals of potential-field data in version 1.0 of the open-source program Monogenic. The monogenic vector of a generic function is calculated in the wavenumber domain and then transformed back into the space domain to find the monogenic signal attributes. We compare the use of the nonscale monogenic signal with the Poisson’s scale-space monogenic signal in magnetic data. This comparison shows that the latter can produce better results as an edge detection filter. The implementation of the monogenic signal can be used to enhance other geophysical data, such as seismic, ground-penetrating radar, gravity, multiple-component gravity gradiometry, and magnetic gradient data.