复杂背景下红外弱小目标检测算法研究

 复杂背景下低信噪比弱小目标的检测是红外预警系统中的重点和难点。为解决红外图像中杂波干扰多、目标信噪比低等问题，提出一种非线性空间滤波的目标检测方法。该算法在传统线性空间滤波算法的基础上，通过对预测点周围4个象限的背景灰度值进行计算，并动态地调节阈值，以达到突出小目标的目的。试验结果表明：当背景包含较多复杂因素时，采用非线性空间滤波的检测方法可有效地抑制杂波，实现弱小目标的提取，与线性滤波算法结果相比较，虚警数降低了3/4，且易于工程实现。

Infrared small target detection under complex background

Small target detection in complex background is a critical technology in the infrared warning system. Aiming at the problems that there is clutter interference in infrared image and the targets signal-to-noise ratio is low, this paper presents a non-linear spatial filtering detection method. Based on traditional linear spatial filter algorithm, the algorithm calculates the gray value around the four quadrants of the potential target, and adjusts the dynamic threshold properly. The results show that when the background contains more complex factors, the non-linear spatial filtering method can effectively suppress the clutter to achieve the extraction of the weak target. Compared with the results of linear filtering algorithm, this algorithm decreases the number of false alarms by 3/4, and has easy engineering realization.