TRUE), and is the same size as the input NDF.
TRUE, bad pixels are excluded from the data sum for each output pixel, and the associated weight for the output pixel is reduced appropriately. The supplied PSF is normalised to a total data sum of unity so that the output NDF has the same normalisation as the input NDF. If NORM is
FALSE, bad pixels are replaced by the mean value and then included in the convolution as normal. The normalisation of the supplied PSF is left unchanged, and so determines the normalisation of the output NDF.
!) value means using the title of the input NDF.
TRUE, then this parameter may be used to determine the number of good pixels that must be present within the smoothing box before a valid output pixel is generated. It can be used, for example, to prevent output pixels from being generated in regions where there are relatively few good pixels to contribute to the smoothed result.
By default, a null (
!) value is used for WLIM, which causes the pattern of bad pixels
to be propagated from the input image to the output image unchanged. In this case,
smoothed output values are only calculated for those pixels which are not bad in the
If a numerical value is given for WLIM, then it specifies the minimum total weight
associated with the good pixels in the smoothing box required to generate a good output
pixel (weights for each pixel are defined by the normalised PSF). If this specified
minimum weight is not present, then a bad output pixel will result, otherwise a
smoothed output value will be calculated. The value of this parameter should lie
between 0.0 and 1.0. A value of
0.0 will result in a good output pixel being created
even if only one good input pixel contributes to it. A value of
1.0 will result in a
good output pixel being created only if all the input pixels which contribute to it are
good. See also Parameter NORM.
The algorithm used is based on the multiplication of the Fourier transforms of the input image and PSF image.
A PSF can be created using the PSF command or MATHS if the PSF is an analytic function.
All non-complex numeric data types can be handled. Arithmetic is performed using double-precision floating point.