Robust Methods for Signal Parameter Estimation and Image Segmentation

本项目涉及统计信号处理和图像 处理.特别是PI正在开发强大的算法， 相关噪声中的信号参数估计， 在噪声图像中从背景中分割对象。 鲁棒性 重要的是，否则最佳方案可能在 存在统计异常值。 鲁棒信号处理的目标 在这种情况下保持接近最佳性能。 在参数估计领域，计划集中于 在名义上高斯噪声的非线性估计，利用 以前开发的线性估计和估计结果， 独立和弱相关噪声。 在图像分割领域， 将集中在导致鲁棒最大值的图像模型上 后验（MAP）分割算法。 三位评审员组成了一个小组， 好极了 调查人员的职业潜力被认为是 非常出色。 该研究领域与CSP计划非常相关。 强烈推荐两年57924美元的奖励。 这个奖应该是 在87财政年度和88财政年度分别资助了25088美元和32836美元。

This project is concerned with statistical signal processing and image processing. In particular the PI is developing robust algorithms for signal parameter estimation in correlated noise and also for the segmentation of objects from background in noisy images. Robustness is important because otherwise optimal schemes can perform poorly in the presence of statistical outliers. The goal of robust signal processing is to maintain the near optimal performance in such a case. In the parameter estimation area, it is planned to concentrate on nonlinear estimation in nominally Gaussian noise, making use of previously developed results in linear estimation and estimation in independent and weakly dependent noise. In the image segmentation area, the concentration will be on image models that result in robust maximum a posteriori (MAP) segmentation algorithms. The three reviewers assembled in a panel rated this proposal as Excellent. The investigators career potential is thought to be outstanding. The area of research is quite relevant to the CSP program. A two-year award of $57924 is highly recommended. This award should be funded at $25088 in FY87 and $32836 in FY88.