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Basic Information on smooth
Task: smooth
Purpose: Convolve an image (in the image domain) with a 2-D Gaussian
Categories: analysis
SMOOTH is a MIRIAD task that convolves an image by an elliptical
Gaussian or a boxcar the hard way. The convolving Gaussian and
boxcar have peaks of unity. Additional scaling is provided by
the keyword "scale"
By default, SMOOTH will mask pixels in the output image if
there are more masked pixels than unmaked pixels in the
Gaussian convolution area. This means that pixels which were
maked in the input may be unmasked in the output.
Key: in
The input image. Wild card expansion is supported, no default.
Key: out
The output image. No default.
Key: type
Specifies the type of function to convolve by. Should
be one of
"gaussian" Gaussian at arbitrary position angle
"boxcar" Boxcar oriented in x and y directions. Note
that the full width is rounded up to be an
odd number of pixels.
Default is gaussian. Minimum match is active.
Key: fwhm
The Gaussian FWHM along the major and minor axes or the boxcar
full widths in the x and y directions (all in arcseconds).
The image pixel increments are assumed to be in radians.
No default.
Key: pa
The position angle in degrees CCW from North of the major axis
of the Gaussian. Not used for boxcar smoothing.
Default is 0.0.
Key: scale
If unset, then SMOOTH will attempt to make the units of the
smoothed image be Jy/beam for Gaussian convolution. If 0.0,
then the convolution integral is scaled (multipled) by the
inverse of the volume of the convolving function. Otherwise,
the integral is scaled by "scale"
Key: options
"nocheck" By default, blanked input pixels do not contribute
to the convolution sum. If you set NOCHECK then blanked
input pixels are not checked for (but the output image is
blanked around the unconvolved edge, and wherever the input
image is blanked).
"force" Force masking of pixels in the output image which
are masked in the input image.
Revision: 1.6, 2021/06/02 04:45:09 UTC
Generated by miriad@atnf.csiro.au on 02 Jun 2021