一种改进的多向梯度红外小目标检测方法

红外小目标检测技术是红外搜索与跟踪系统（IRST）、红外警戒等系统中的一项关键技术。常规小目标检测算法存在对椒盐噪声、高亮背景边缘敏感等不足之处,针对上述问题,对天空背景红外弱小目标的几何和灰度特性进行了深入研究,在此基础上提出了基于多向梯度的红外小目标检测的新方法,采用了一种非对称的梯度算子,重新定义了梯度检测函数,提高了对小目标的响应。仿真实验结果表明,该方法能够较好地抑制高亮云层边缘和椒盐噪声,保证了较高的检测率和较低的虚警率,又便于在FPGA上实现,满足系统对实时性的要求。

An Improved Detection Method of The Infrared Small Target

The detection technique for infrared small targets is a key part of an infrared searching and tracking(IRST) system or an infrared surveillance system.The conventional methods are too sensitive to salt and pepper noise and the highlight edges of the background.The geometry and grey level characteristics of infrared small targets in sky background were researched.A new method of detecting infrared small targets was proposed based on multi-degree and orientation gradient.The simulation experiment results show the method could restrain the salt and pepper noise and the highlight edges of the background.The high detection rate and a low false alarm rate are obtained.This method also could be implemented in FPGA to satisfy the real-time requirement.