Motion Compensated Processing of Image Sequences

本文的研究重点是基于模型的图像序列 估计和恢复和实施使用多- 处理. 图像估计是使用扩展的 降阶模型卡尔曼滤波和位移估计 参数 模拟退火型算法在 解决了由此产生的估计问题。 修复体 通过将速度约束明确地 3D时空模型。 最后，算法是 在DAP和MASPAR等大规模并行计算机上实现 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.