Convolution Filter

Use the Convolution Filter option (FILTER GX) to apply a convolution filter on a channel. The filter can be defined in a filter file or as a comma delimited string.

The filter option is available from the following locations/menus:

• Database Tools > Filters
• Database Tools > Array Channels > Convolution Filter > Along Line
• Moving Platform Gravity > Filters

Convolution Filter dialog options

Channel to filter	Name of the Input channel Script Parameter: FILTER.IN
Output channel	Name of the output filtered channel. Script Parameter: FILTER.OUT
Filter file	Filter containing the filter coefficients. Script Parameter: FILTER.FILE
Or Filter (c1,c2,...)	The alternative to providing the filter coefficients in a file is to enter them here, comma delimited. User defined coefficients take precedence over a specified filter file. Script Parameter: FILTER.OR

Application Notes

The FILTER GX can be used to apply any even or odd-length convolution filters to a channel. If the filter has an even length, the resulting filtered channel will start one-half fiducial increment past the start of the original data.

If the sum of the filter coefficients is 1, the filtered channel will be of the same order as the input channel. If the sum of the filter coefficients is 0, the DC component is removed and the output will have a zero base.

If the filter has an even length, the resulting filtered channel will start one-half fiducial increment past the start of the original data.

Maximum entropy prediction is used to pad data to the ends of the channel data, and to fill holes in the data. The ends of the data and holes are removed after applying the filter.

A filter file must contain one filter coefficient on each line. Comment lines (those beginning with a '/' character) and blank lines are skipped.

Standard filters provided with the installation:

• The Fraser filter is typically used on VLF data and yields effectively an enhanced 1st spatial derivative of the data.

• The Laplace filter yields the 2nd spatial derivative of the data, and helps highlight regions of rapid intensity change and is therefore often used for edge detection.

• The Savitzky-Golay filter removes the background chatter from the data.

FraserP4.FLT	Positive even Fraser filer (-1,-1,1,1)
FraserM4.FLT	Negative even Fraser filer (1,1,-1,-1)
FraserP5.FLT	Positive odd Fraser filer (-.5,-1,0,1,.5)
FraserM5.FLT	Negative odd Fraser filer (.5,1,0,-1,-.5)
LAPLACE.FLT	Laplace filter (-0.5,1,-0.5)
Savitzky-Golay_4_5_5.flt	Symmetrical Savitzky-Golay noise filter of power 4 (0.0415,-0.105,-0.023,0.140,0.280,0.333,0.280,0.140,-0.023,-0.105,0.0415)