  When recording spectra from the ground, atmospheric turbulence causes
degradation of the spatial resolution. We present a data reduction method that
restores the spatial resolution of the spectra to their undegraded state. By
assuming that the point spread function (PSF) estimated from a strictly
synchronized, broadband slit-jaw camera is the same as the PSF that spatially
degraded the spectra, we can quantify what linear combination of undegraded
spectra is present in each degraded data point. The set of equations obtained
in this way is found to be generally well-conditioned and sufficiently diagonal
to be solved using an iterative linear solver. The resulting solution has
regained a spatial resolution comparable to that of the restored slit-jaw
images.
