A Robust Algorithm for the Pointing Refinement and Registration of   Astronomical Images
  We present a generic algorithm for performing astronomical image registration and pointing refinement. The method is based on matching the positions and fluxes of available point sources in image overlap regions. This information is used to compute a set of image offset corrections by globally minimizing a weighted sum of all matched point-source positional differences in a pre-specified reference image frame. A fast linear sparse matrix solver is used for the minimization. From these corrections, the pointings and orientations of images can be refined in either a relative sense where pointings become fixed (registered) relative to a single input image, or, in an absolute sense (in the ICRS) if absolute point source information is known. The latter provides absolute pointing refinement to an accuracy depending on the robustness of point source extractions, match statistics, and accuracy of the astrometric catalog used. The software is currently used in the Spitzer image processing pipelines, although it is adaptable to any astronomical imaging system which uses the FITS image format and WCS pointing standard. We test the algorithm using Monte Carlo simulations and compare them to image data acquired with the Infrared Array Camera (IRAC) on board the Spitzer Space Telescope. 
Frank J. Masci, David Makovoz and Mehrdad Moshir (Spitzer Science   Center, California Institute of Technology)