Improved edge detection mapping through stacking and integration: a case study in the Bathurst Mining Camp

Abstract

Airborne geophysical surveys provide spatially continuous regional data coverage, which directly reflects subsurface petrophysical differences and thus the underlying geology. A modern geologic mapping exercise requires the fusion of this information to complement what is typically limited regional outcrop. Often, interpretation of the geophysical data in a geological context is done qualitatively using total field and derivative maps. With a qualitative approach, the resulting map product may reflect the interpreter's bias. Source edge detection provides a quantitative means to map lateral physical property changes in potential and non‐potential field data. There are a number of Source edge detection algorithms, all of which apply a transformation to convert local signal inflections associated with source edges into local maxima. As a consequence of differences in their computation, the various algorithms generate slightly different results for any given source depth, geometry, contrast, and noise levels. To enhance the viability of any detected edge, it is recommended that one combines the output of several Source edge detection algorithms. Here we introduce a simple data compilation method, deemed edge stacking, which improves the interpretable product of Source edge detection through direct gridding, grid addition, and amplitude thresholding. In two examples, i.e., a synthetic example and a real‐world example from the Bathurst Mining Camp, New Brunswick, Canada, a number of transformation algorithms are applied to gridded geophysical data sets and the resulting Source edge detection solutions combined. Edge stacking combines the benefits and nuances of each Source edge detection algorithm; coincident or overlapping and laterally continuous solutions are considered more indicative of a true edge, whereas isolated points are taken as being indicative of random noise or false solutions. When additional data types are available, as in our example, they may also be integrated to create a more complete geologic model. The effectiveness of this method is limited only by the resolution of each survey data set and the necessity of lateral physical property contrasts. The end product aims at creating a petrophysical contact map, which, when integrated with known lithological outcrop information, can be led to an improved geological map.

A Comparative Study on the Method of Extracting Edge and Contour Information of Multifunctional Digital Ship Image

“…1(e1) and Fig. 1(e2) that it still contains a certain noise in the edge extraction by the method of section C and the method of reference [13], resulting in the incomplete extraction of edge and contour information, which cannot get more accurate edge information [18][19][20][21][22]. Compared with the other two methods, the proposed method has obvious advantages, and the noise in the original multimedia digital ship image is removed well, retaining better detail information for the subsequent image segmentation and edge and contour information extraction.…”

“…[13] (c2) Denoising method in reference [13] (d1) The results of edge extraction by the method in reference [13] (d2) The results of edge extraction by the methodin reference [13] (e1) The results of edge extraction by the proposed method The comprehensive comparative analysis of Figure 1 can be seen, the denoising effect of wavelet transform method used in section A and Gaussian filter method used in reference [13] for multimedia digital ship image denoising is not ideal, seriously affect the subsequent image processing. It can be seen from the edge extraction effect of Fig.…”

“…The edge and contour information extraction of multifunctional digital ship image, has become one of the hot research topics [10][11][12]. In reference [13], a method of extracting edge and contour information of multifunctional digital ship image based on self-enhancement is proposed. Firstly, the multifunctional digital image is subjected to make smoothing denoising by small-scale Gaussian filtering, and then the Canny edge detection operator is used to obtain the feature guidance information of the multifunctional digital image.…”

A multi‐parameter approach for recognition of anthropogenic noise in aeromagnetic data collected over populated areas: Erzgebirge, Germany

“…A commonly applied procedure in magnetic and gravity data analysis is an edge detection filter. The intent of the edge filter is to derive an estimate of the horizontal location of the boundary of a magnetic anomaly source body (Pilkington & Keating, 2004;Tschirhart & Morris, 2015;Pilkington & Tschirhart, 2017). Typically, this approach is used to render a pseudo-geological contact map from the observed magnetic data.…”

Imaging sedimentary basins from high-resolution aeromagnetics and texture analysis

“…The availability of high-resolution aeromagnetic data has made their application an important tool for mapping regional geology (Balsley, 1952;Pilkington, 1998;Pilkington and Keating, 2004). This is especially the case in areas with limited and sparse outcrop where it becomes necessary to correlate interpreted magnetic rock packages with exposed lithologies (Aitken and Betts, 2009;Gunn et al, 1995;Tschirhart and Morris, 2015). While aeromagnetics is often applied for the interpretation of the magnetic basement (Cordell and Grauch, 1985;Isles and Rankin, 2013;Steenland, 1963), the compilation of higher-resolution gridded aeromagnetic data has also enabled other types of anomaly patterns to be used for qualitative interpretations of near-surface features (Nabighian et al, 2005).…”