Simultaneous Recursive Displacement Estimation and Restoration of Image Sequences

In this paper, we develop a recursive model-based maximum a posteriori (MAP) estimator that simultaneously e& timates the displacement vector field (DVF) and intensity field from a noisy-blurred image sequence. Current motioncompensated spatio-temporal filters treat the estimation of the DVF as a preprocessing step. Thereby, no attempt is made to verify the accuracy of these estimates prior to their use in the filter. By simultaneously estimating these two fields, information is made available to each filter regarding the reliability of estimates that they are dependent upon. Nonstationary models are used for the DVF and the intensity field in the proposed estimator, thus avoiding the smoothing of boundaries present in both. Experimental results are provided which show the effectiveness of the proposed recursive model-based MAP estimator.