强杂波中红外弱点目标检测新算法

New Detection Algorithm of Weak Infrared Point Targets Under Strong Clutter

为解决强杂波中红外弱点目标的检测问题 ,提出了基于小波变换模极值及其位相值的双特征检测算法。通过去掉相邻奇异点形成的模极值链及位相链 ,消除云层、海浪及水天线等强杂波背景 ,提高了单帧点目标的检测能力。模拟实验表明 ,该算法特别适用于低帧率的红外警戒系统 ,可检测信杂比为 2的点目标。

Two features detection algorithm based on the wavelet transform modulus maxima and its phase angle is presented,to resolve the problem of weak infrared point targets detection. The modulus maxima chains and phase chains formed by adjacent singularity are taken out to eliminate the strong clutter of clouds,ocean waves and sea level,enhance the ability of point target detection in single frame.Simulating experimental results shown the algorithm is especially suited for surveillance system of low frame rate and can detect the point targets with signal to clutter ratio equal to 2.