Motion Compensated Processing of Image Sequences

本文的研究重点是基于模型的图像序列估计与恢复以及多处理实现。利用扩展降阶卡尔曼滤波和位移参数估计实现图像估计。研究了模拟退火算法来解决由此产生的估计问题。恢复是通过将速度约束明确地纳入三维时空模型来实现的。最后，算法在大规模并行计算机（如DAP和MASPAR）上实现，这些计算机配置为线性阵列。

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.