多光谱目标探测的波段选择

Wavelength bands selection method of multispectral target detection

利用超光谱数据对多光谱传感器的波段选择提出了一个框架。根据探测理论,导出了一个代价函数,对于区分弱小目标和杂波(光谱分布已知)的探测性能最优的光谱波段来说,可使该函数最小。利用匹配追踪算法找到了一个近似最小的代价函数,从而选出了滤波器。该方法可用于设计多光谱红外搜索跟踪和光电导弹预警传感器。在杂波背景下,对小目标探测的低虚警率和高探测概率来说是至关重要的。

A framework was proposed for the selection of wavelength bands for multispectral sensors by use of hyperspectral reference data. Using the results from the detection theory, a cost function was derived that was minimized by a set of spectral bands optimal in terms of detection performance for discrimination between a class of small rare .targets and clutter with known spectral distribution. An approximate minimizer of cost function is found by using matching pursuit algorithm, and the filters are selected. The method may be used in the design of multispectral infrared search and track and electro-optical missile warning sensors, where a low false-alarm rate and a high-detection probability for detection of small targets against a clutter background are of critical importance.