Robust Methods for Signal Parameter Estimation and Image Segmentation

该项目涉及统计信号处理和图像处理。特别是，PI正在开发稳健的算法，用于相关噪声中的信号参数估计，以及噪声图像中的目标与背景的分割。稳健性很重要，因为在存在统计异常值的情况下，其他最优方案的性能可能会很差。稳健信号处理的目标是在这种情况下保持接近最佳的性能。在参数估计领域，计划集中于名义上的高斯噪声中的非线性估计，利用先前发展的线性估计和独立和弱相依噪声中的估计结果。在图像分割领域，重点将放在能够产生稳健的最大后验概率(MAP)分割算法的图像模型上。聚集在一个小组中的三位评审员将这项提议评为极好。调查人员的职业潜力被认为是突出的。研究领域与CSP方案非常相关。强烈建议设立为期两年的57924美元奖金。这项奖励的资金在87财年为25088美元，在88财年为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.