Optical Pattern Recognition with Spatially Disjoint Signal and Scene Noise

9406922在输入信号和场景噪声存在空间不相交的情况下，在空间重叠的输入信号和场景噪声假设下导出的Javidi匹配滤波函数和最优处理器可能不能很好地执行，并且可能导致非常差的系统性能。这项工作的目的是为空间分离的信号和场景噪声设计新的最优处理器。主要研究人员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、比例、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被包括在该模型中。它旨在对在与目标空间不相交的场景噪声存在的情况下设计的光学模式识别系统进行理论、数值和实验研究。***

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. ***