FRD2P

Description

Applies a reduction to pole filter to a potential field image. The filter is applied in the frequency domain. A 2-D Fast Fourier transformation (FFT) is first applied to the image. After filtering, the image is transformed back to the spatial domain.

Parameters

Name	Type	Length	Value range
Input: Input potential field channel *	Raster port	1 - 1
Output: Output filtered image channel *	Raster port	1 - 1
Source Inclination Angle (deg)	Float	1 - 1	0 - 180 Default: 30
Source Azimuth Angle (deg)	Float	1 - 1	0 - 180 Default: 30
Regional Inclination Angle (deg)	Float	1 - 1	0 - 180 Default: 30
Regional Azimuth Angle (deg)	Float	1 - 1	0 - 180 Default: 30
Report	String	0 - 192	See parameter description

* Required parameter

Parameter descriptions

Input: Input potential field channel

Specifies the input channels containing the potential fields to use in the transformation.

Output: Output filtered image channel

Specifies the output channel to receive the filtered image data.

Source Inclination Angle (deg)

Specifies, in degrees, the inclination angle of the source magnetic field. The default value is 30.0.

Source Azimuth Angle (deg)

Specifies, in degrees, the azimuth angle of the source magnetic field. The default value is 30.0.

Regional Inclination Angle (deg)

Specifies, in degrees, the inclination angle of the regional magnetic field. The default value is 30.0.

Regional Azimuth Angle (deg)

Specifies, in degrees, the azimuth angle of the regional magnetic field. The default value is 30.0.

Report

Specifies where to direct the generated report.

Available options are:

• LOG: generates a report on the terminal (default)
• <modulename.RPT>: appends a report to the module's RPT file
• DISK: generates a report on file "IMPRPT.LST"

Details

FRD2P applies the reduction to pole filter to a potential field image. The filter is applied in the frequency domain. The image is transformed using a 2-D Fast Fourier transformation (FFT), then transformed back to the spatial domain after filtering.

This function is most efficient if the input window has dimensions of a power of 2; otherwise, FCONT must pad extra rows and columns to force the image dimensions a power of 2.

Algorithm

The input image is first transformed to frequency domain using 2-D FFT. The dimensions of the transformed image are power of 2 and are at least as large as the input image dimensions. After applying the filter, the frequency image is transformed back to the spatial domain and truncated to the input image size.

The reduction to pole filter has the following form:

        f^2 / [c1 f + i(a1 u + b1 v)] [c2 f + i(a2 u + b2 v)]

The filter gain at u=v=0 is undefined. A value of 1.0 is inserted. The resolution of u, v are given as:

        Delta_u = 1/(SizeU * Delta_x)
        Delta_v = 1/(SizeV * Delta_y)