Robust Methods for Signal Parameter Estimation and Image Segmentation

信号参数估计和图像分割的鲁棒方法

• 批准号: 8710871
• 负责人: Patrick Kelly
• 金额: $ 5.79万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-07-15 至 1989-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8710871&HistoricalAwards=false
• 关键词: Robust; Methods; Signal; Parameter; Estimation

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.

该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，用于相关噪声中的信号参数估计，以及噪声图像中的背景中的对象分割。 稳健性很重要，因为否则最佳方案在存在统计异常值的情况下可能表现不佳。 鲁棒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，计划集中于名义高斯噪声中的非线性估计，利用先前开发的线性估计和独立和弱相关噪声估计中的结果。 在图像分割领域，重点将放在图像模型上，从而产生鲁棒的最大后验（MAP）分割算法。 组成小组的三位评审员将该提案评为“优秀”。 调查员的职业潜力被认为是突出的。 该研究领域与 CSP 计划非常相关。 强烈推荐 57924 美元的两年奖励。 该奖项在 2087 财年的资助金额为 25088 美元，在 2088 财年的资助金额为 32836 美元。