公开(公告)号：US20150023553A1

公开(公告)日：2015-01-22

申请号：US14296653

申请日：2014-06-05

Applicant: U.S. Army Research Laboratory ATTN: RDRL-LOC-I

Inventor： Dalton S. Rosario ,  Joao M. Romano ,  James P. McCarthy

IPC: G06K9/62 ,  G06K9/00

CPC classification number: G06K9/00624 ,  G06K9/209 ,  G06K9/6289

Abstract: A methodology for detecting image anomalies in a target area for classifying objects therein, in which at least two images of the target area are obtained from a sensor representing different polarization components. The methodology can be used to classify and/or discriminate manmade objects from natural objects in a target area, for example. A data cube is constructed from the at least two images with the at least two images being aligned, such as on a pixel-wise basis. A processor computes the global covariance of the data cube and thereafter locates a test window over a portion of the data cube. The local covariance of the contents of the test window is computed and objects are classified within the test window when an image anomaly is detected in the test window. For example, an image anomaly may be determined when a matrix determinant ratio of the local covariance and the global covariance exceeds a probability ratio threshold. The window can then be moved, e.g., by one or more pixels to form a new test window in the target area, and the above steps repeated until all of the pixels in the data cube have been included in at least one test window.

Abstract translation: 一种用于检测目标区域中的图像异常的方法，用于对其中的对象进行分类，其中从表示不同偏振分量的传感器获得目标区域的至少两个图像。 例如，该方法可以用于将人造物体与目标区域中的自然物体分类和/或区分开。 从所述至少两个图像构建数据立方体，其中所述至少两个图像被对准，诸如在像素方面的基础上。 处理器计算数据立方体的全局协方差，然后在数据立方体的一部分上定位测试窗口。 在测试窗口中检测到图像异常时，计算测试窗口内容的局部协方差，并将对象分类到测试窗口内。 例如，当局部协方差和全局协方差的矩阵行列式比率超过概率比阈值时，可以确定图像异常。 然后可以例如通过一个或多个像素来移动窗口，以在目标区域中形成新的测试窗口，并重复上述步骤，直到数据立方体中的所有像素已被包括在至少一个测试窗口中。