Non-linear Filter Along Array

Use the Non Linear Filter > Along Array menu option from Database Tools > Array Channels, (VANLFILT GX), to apply a non-linear filter to an array channel along the array (row). Non-linear filters are very good for removing high amplitude and short wavelength noise from data.

Non Linear Filter Along Array dialog options

Input channel	Name of the Input Channel. It must be an array channel. Script Parameter: VANLFILT.INCH
Output channel	Name of the output channel (created if does not exist). If the 'Output channel' entry is empty, filter results will be saved in the same input channel and the original data in the input channel will be overwritten. When an output channel name is given, the channel will be created if it does not exist in the database. However, if the output channel already exists in the database, it must have the same array size as the input channel. Script Parameter: VANLFILT.OUTCH
Filter width	Maximum width of the noise in data points. Features that are wider than this width will not be changed. Default is 1. Script Parameter: VANLFILT.WIDTH
Filter tolerance	Only noise of greater amplitude than this tolerance will be changed. Script Parameter: VANLFILT.TOL

Application Notes

VANLFILT is ideal for removing very short wavelength, but high amplitude features from data. It is often thought of as a noise spike-rejection filter, but it can also be effective for removing short wavelength geological features, such as signal from surficial features.

VANLFILT uses a method similar to that described by Naudy and Dreyer, 1968, to locate and remove data that is recognised as noise. The algorithm is 'non- linear' because it looks at each data point and decides if that data is noise or valid signal. If the point is noise, it is simply removes and replaced by an estimate based on surrounding data points, and parts of the data that are not considered noise are not modified at all. Linear filters lack such a decision capability and therefore modify all data.

The decision algorithm is based on the width of features in the data and the amplitude of those features relative to a local background. In order to be considered noise, a feature must be narrower than a specified width and of greater amplitude than a specified amplitude tolerance. The width must be specified in number of data points. For example, single spikes in the data will have a width if 3 points. The non-linear filter amplitude tolerance, if specified, uses the actual data units, for example, 5 gamma. If no tolerance value is specified, the default value is set to equal a percentage of the range of data.