Multiframe resolution enhancement methods are used to estimate a high-resolution video still (HRVS) from several low-resolution image sequence frames, provided that objects within the video sequence move with subpixel increments. Estimating accurate subpixel-resolution motion vectors is a challenging, albeit critically important component of super-resolution enhancement algorithms. A Bayesian motion estimation technique is proposed which models the motion field with a discontinuity-preserving prior. The method is related to Horn-Schunck (1981) optical flow estimation, except that the discontinuity-preserving prior can allow abrupt changes within the motion field without the use of line processes. Simulations compare the high-resolution video stills which result from using the subpixel motion vectors calculated by block matching and the proposed Bayesian motion estimation technique.
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