The use of fractal dimension estimators for enhancing airborne magnetic data

Abstract

Airborne magnetic data is routinely enhanced by amplitude based filters such as horizontal and vertical derivatives. Texture is defined as the spatial distribution of amplitudes over a region. Textural analysis provides a possible alternative method of data enhancement. This paper investigates the potential of using fractal dimension for quantifying texture and highlighting textural contrasts in airborne magnetic data. Profiles have been created by combining theoretical data with fractal dimensions (FD) of 1.1, 1.3 and 1.5. Estimates of FD using the semi-variogram and variation methods clearly distinguish between sections of the profiles with different theoretical FD. Fractal dimension estimates made on a real airborne magnetic profile, using the variation method, clearly define two regions of visible textural contrast. A series of other variations in the estimated FD suggests that the method is able to resolve subtle contrasts that are not easily detected visually. The semi-variogram method of FD estimation is not able to resolve the obvious textural contrasts in real data, a result that is perhaps due to the stochastic nature of this methodology. The variation method has been used to estimate FD on a series of airborne magnetic profiles. This profile data was then gridded to generate an image of FD that moderately improves structural resolution. Whilst more work needs to be carried out, it is obvious that estimates of FD do detect textural contrasts in both theoretical and real data, and that this information can be used to enhance aeromagnetic data.