红外搜索系统中弱小目标检测算法研究

Point target detection in infrared search system

复杂背景下低信噪比弱小目标的检测是红外搜索系统中的重点和难点,为解决红外搜索系统中杂波干扰多、目标信噪比低等问题,提出一种模板匹配滤波的目标检测方法。该算法在预测背景的同时,通过对图像背景灰度值进行动态的阈值处理,自适应地进行背景抑制。当背景包含较多复杂因素时,采用模板匹配滤波的目标检测方法,消除背景抑制后的残留杂波,实现弱小目标的提取。试验结果表明:当场景较复杂且图像信噪比较低时,使用该算法处理后可使图像信噪比达到4dB以上,从而提高了弱小目标的检测概率。

Aiming at the effective detection of low signal-to-noise ratio（SNR） point target and the analysis capabilities in clutter background,a template matching filtering method is proposed.The algorithm uses dynamic threshold processing of background gray values,suppresses the background adaptively.When the background is complex,the template matching filtering method for target detection is used to remove the large areas of residual clutter after background suppression,and the extraction of weak target is achieved.The experiment results show that the SNR can be better than 4 dB when the scene is complex,and the detection probability of point targets is increased.