论文标题
多变量T分布的背景中的经过修改的替换模型目标的广义似然比测试探测器
Generalized likelihood ratio test detector for a modified replacement model target in a multivariate t-distributed background
论文作者
论文摘要
在多光谱图像中的子像素靶标的广义似然比检测器（GLRT）检测器中得出了封闭形式的表达，其面积和亮度都是未知的。该表达式将先前的结果（假设高斯背景分布）扩展到较胖的椭圆形（EC）多元T分布式背景。具有模拟数据的数值实验表明，基于EC的检测器的表现优于基于高斯的检测器，与其他基于EC的检测器相比，新检测器的相对性能取决于目标强度和背景闭合的状态。
A closed-form expression is derived for the generalized likelihood ratio test (GLRT) detector of a subpixel target in a multispectral image whose area and brightness are both unknown. This expression extends a previous result (which assumed a Gaussian background distribution) to a fatter tailed elliptically-contoured (EC) multivariate t-distributed background. Numerical experiments with simulated data indicate that the EC-based detector outperforms the simpler Gaussian-based detectors, and that the relative performance of the new detector, compared to other EC-based detectors, depends on the regime of target strength and background occlusion.
