  Atmospheric optical turbulence can be a significant source of image
degradation, particularly in long range imaging applications. Many turbulence
mitigation algorithms rely on an optical transfer function (OTF) model that
includes the Fried parameter. We present anisoplanatic tilt statistics for
spherical wave propagation. We transform these into 2D autocorrelation
functions that can inform turbulence modeling and mitigation algorithms. Using
these, we construct an OTF model that accounts for image registration. We also
propose a spectral-ratio Fried parameter estimation algorithm that is robust to
camera motion and requires no specialized scene content or sources. We employ
the Fried parameter estimation and OTF model for turbulence mitigation. A
numerical wave-propagation turbulence simulator is used to generate data to
quantitatively validate the proposed methods. Results with real camera data are
also presented.
