Image Convolution(imsmooth)

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6.12 Image Convolution(imsmooth)

A data cube can be smoothed across spatial dimensions with imsmooth. The inputs are:

#  imsmooth :: Smooth an image or portion of an image
imagename           =         ’’        #  Name of the input image
kernel              =    ’gauss’        #  Type of kernel to use: gaussian or
                                        #   boxcar.
     major          = ’2.5arcsec’       #  Major axis for the kernels, default
                                        #   direction is along y-axis.
     minor          = ’2.0arcsec’       #  Minor axis in gaussian and boxcar
                                        #   kernels
     pa             =     ’0deg’        #  Position angle for gaussian kernel
     targetres      =      False        #  If gaussian kernel, specified
                                        #   parameters are to be resolution of
                                        #   output image (True) or parameters of
                                        #   gaussian to convolve with input image
                                        #   (False).

region              =         ’’        #  Image Region or name.  Use viewer
box                 =         ’’        #  Select one or more box regions
chans               =         ’’        #  Select the spectral channel range
stokes              =         ’’        #  Stokes parameters to image
                                        #   (I,IV,IQU,IQUV)
mask                =         ’’        #  Mask used for selecting the area of
                                        #   the image
outfile             =         ’’        #  Output, smoothed, image file name
async               =      False        #  If true the taskname must be started

where the cube/image imagename will be convolved with a kernel defined in the kernel keyword. Available kernels are ’gauss’ and ’boxcar’. Both of these kernels need the major and minor axes sizes as input, the Gaussian kernel smoothing also requires a position angle. By default, the kernel size defines the kernel itself, i.e. the data will be smoothed with this kernel. If the targetres parameter for Gaussian kernels is set to ’True’, major and minor axes will be those from the output resolution.

Examples:

1) smoothing with a gaussian kernel 20” by 10”

imsmooth( imagename=’my.image’, kernel=’gauss’, major=’10arcsec’, minor=’10arcsec’)

2) Smoothing using pixel coordinates and a boxcar kernel.

imsmooth( imagename=’new.image’, major=’20pix’, minor=’10pix’, kernel=’boxcar’)

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