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Enhancement of magnetic data by logarithmic transformation

McMaster University, Hamilton, Ontario, Canada

George Leblanc

Canada Centre for Aerospace Research, National Research Council, Ottawa, Ontario

Corresponding author: morriswa@mcmaster.ca

The first 20% of the full text of this article appears below.

A common problem encountered when displaying magnetic data as a color image is that small amplitude variations, which may have geologic significance, might be lost due to the large dynamic range of the whole data set. The human eye is capable of distinguishing only a limited range of variations within the color spectrum. Enhancement of the low-amplitude features is usually achieved through some type of image transform. By far the simplest approach to this problem is modification of the input limits of the datA—i.e., the operator selects a subset of the full dynamic range. To investigate the full complexity of information present with this technique often requires the operator to produce a number of different amplitude-based maps because the data above and below the selected amplitude window will be monochromatic (i.e., all blue or red below or above the window, respectively). Significant image enhancement can be achieved through equalization of the number of pixels within each color band. This procedure, termed histogram equalization, increases the image resolution in portions of the spectrum where there are large numbers of observations. It may not, however, increase the resolution of low-amplitude values, even when the low amplitudes are within the region with the highest percentage of observations. Histogram equalization serves to provide approximately equal distribution color coverage in the image while preserving the absolute amplitude information.

Many publications have demonstrated that geologically relevant information is often present in the low-amplitude portion of the amplitude spectrum of the magnetic data. This problem has been addressed through the application of automatic gain control (AGC), which transforms signals of variable amplitude into waveforms of semiconstant amplitude by estimating the local rms gain within a moving window. As noted by Milligan and Gunn (AGSO, 1997), this procedure "is extremely useful for structural mapping because" the AGC . . . [Full Text of this Article]