The basic Filters tool lets you apply several simple filters to your image. This can be very useful for data denoising; however, the real measured data will get altered in the process, so great care should be taken not to destroy important features of the image.
All filters alter the data based on the values in the neighbourhood of the filtered pixel. For some filters the size and shape of the neighbourhood is fixed. For most, however, the size can be controlled with parameter Size. Apart from Gaussian-based filters (described below) the size determines the diameter of the neighbourhood in pixels. It is thus advisable to use filters of odd sizes because their effect is symmetric.
By default, these filters will be applied to the entire image. However, you can apply a filter to a specific region within your image by selecting it with the mouse. This can be useful for correcting poorly measured areas within a good image.
It is also possible to limit the area by masking. In this case the mask determines the active pixels whose values will be modified by the filter. Pixels in the neighbourhood of the active area can however still enter the calculation passively, i.e. their values can influence the result.
Several of the basic filters can be used for simple denoising and defect removal. Further defect marking and removal functions are described in section Data Editing, see for instance Mask of Outliers and Remove Data Under Mask. More advanced denoising functions in Gwyddion, for example DWT denoising and FFT filtering, are described in section Extended Data Editing.
Discrete convolutions with arbitrary kernels up to 9 × 9 can be performed using Convolution Filter (see Image Convolution for convolution of two images).
The Divisor entry represents a common factor all the coefficients are divided by before applying the filter. This allows to use denormalized coefficients that are often nicer numbers. The normalization can be also calculated automatically when automatic is checked. When the sum of the coefficients is non-zero, it makes the filter sum-preserving, i.e. it normalizes the sum of coefficients to unity. When the sum of the coefficients is zero, the automatic factor is simply let equal to 1.
Since many filters used in practice exhibit various types of symmetry, the coefficients can be automatically completed according to the selected symmetry type (odd, even). Note the completion is performed on pressing Enter in the coefficient entry.
In a fresh installation only a sample Identity filter is present (which is not particularly useful as it does nothing). This filter cannot be modified, to create a new filter use the New button on the Presets page.