FEATHER Algorithm

      FEATHER use the following steps
    - Make oversampled Fourier Transform of both HIGHres and LOWres images
    - Compute the truncation function f(r)
    - Make the Truncated compact Fourier Transform, f(r) x T(LOW)
    - Make the complement long baseline Fourier Transform, (1-f(r)) x T(HIGH)
    - Sum them T(ALL) = R x f(r) x T(LOW) + (1-f(r)) x T(HIGH)
         where R is a scale factor taken from FEATHER_RATIO
    - Make the inverse Fourier Transform
    - Truncate the resulting image to original size and Mask of the HIGHres
      images

    If LOWres is a single-dish image, f(r) should normally be the beam  of  that
    telescope  to use optimal Signal-to-noise ratio from that data set. However,
    because of pointing errors and other calibration  issues  such  as  spectral
    baseline,  using a sharper transition function gives better results. FEATHER
    uses the function
        f(r) = exp(-(r/Radius)^Expo)
    where Radius is taken from FEATHER_RADIUS and Expo from FEATHER_EXPO.