论文标题
在复杂背景下基于各向同性约束的红外小目标检测
Infrared small target detection based on isotropic constraint under complex background
论文作者
论文摘要
红外搜索和跟踪（IRST）系统在国防领域广泛关注和应用。在复杂背景下的小目标检测是系统算法开发中非常具有挑战性的任务。靶标的低信噪比（SCR）和不规则背景杂物引起的干扰使得难以获得准确的结果。在本文中，小目标被认为具有两个高对比度和各向同性的特征，我们提出了一种受各向同性约束的多层灰差（MGD）方法。首先，可疑区域是通过MGD获得的，然后计算原始图像的Hessian矩阵的特征值以获得每个区域的各向同性参数。最后，这些区域不符合各向同性约束条件。实验表明，就信噪比增益（SCRG）和接收器操作特征（ROC）曲线而言，该提出的方法具有有效且优于几种常见方法。
Infrared search and tracking (IRST) system has been widely concerned and applied in the area of national defence. Small target detection under complex background is a very challenging task in the development of system algorithm. Low signal-to-clutter ratio (SCR) of target and the interference caused by irregular background clutter make it difficult to get an accurate result. In this paper, small targets are considered to have two characteristics of high contrast and isotropy, and we propose a multilayer gray difference (MGD) method constrained by isotropy. Firstly, the suspected regions are obtained through MGD, and then the eigenvalues of the original image's Hessian matrix are calculated to obtain the isotropy parameter of each region. Finally, those regions do not meet the isotropic constraint condition are suppressed. Experiments show that the proposed method is effective and superior to several common methods in terms of signal-to-clutter ratio gain (SCRG) and receiver operating characteristic (ROC) curve.
