The detection of circular features in irregularly spaced data

Abstract

Geophysical potential field data are usually interpolated onto a regular grid before data enhancement and interpretation. Unfortunately the inherent smoothing in the gridding process can be sufficient to distort or even hide small-amplitude anomalies that are nevertheless of economic importance. Circular features may correspond to anomalies from Kimberlite pipes or meteorite impact craters, and are therefore of considerable interest. The Hough transform is a useful tool for the detection of circular features in gridded data, but its sensitivity to the choice of radius means that it performs poorly when applied to ungridded data. A modified version of the Hough transform which works well on ungridded data is described here, and demonstrated on gravity data from South Africa.