The focus of this research is on model-based image sequence estimation and restoration and implementation using multi- processing. The image estimation is achieved using extended reduced order model Kalman filter and estimates of displacement parameters. Simulated annealing type algorithms are explored in solving the resulting estimation problem. The restoration is achieved by the incorporation of velocity constraints explicitly into the 3D space-time model. Finally, the algorithms are implemented on massively parallel computers such as DAP and MASPAR configured as a linear array.
