Optical Pattern Recognition with Spatially Disjoint Signal and Scene Noise

具有空间不相交信号和场景噪声的光学模式识别

• 批准号: 9406922
• 负责人: Bahram Javidi
• 金额: $ 5万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-09-15 至 1996-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9406922&HistoricalAwards=false
• 关键词: Optical; Pattern; Recognition; Spatially; Disjoint

9406922 Javidi Matched filter functions and optimum processors derived under the spatially overlapping input signal and scene noise assumption may not perform well in the presence of spatially disjoint input signal and scene noise, and could lead to very poor system performance. The purpose of this work is to design new optimum processors for spatially disjoint signal and scene noise. The principal investigator will consider a general model of a target in non- overlapping input scene noise where the target may include distortions such as unknown illumination, scale, rotation, etc. Overlapping noise on the target due to detector noise or other statistical fluctuations will be included in this model. It is intended to conduct theoretical, numerical, and experimental investigation of the optical pattern recognition systems which are designed in the presence of scene noise that is spatially disjoint with the target. ***

在空间重叠的输入信号和场景噪声假设下导出的匹配滤波器函数和最佳处理器在存在空间不相交的输入信号和场景噪声的情况下可能不能很好地执行，并且可能导致非常差的系统性能。 本文的目的是设计新的空间不相交信号和场景噪声的最佳处理器。 主要研究者将考虑非重叠输入场景噪声中目标的一般模型，其中目标可能包括诸如未知照明、缩放、旋转等失真。 由于探测器噪声或其他统计波动导致的目标上的重叠噪声将包括在该模型中。 它的目的是进行理论，数值和实验研究的光学模式识别系统，设计在存在的场景噪声是空间不相交的目标。 ***