基于光流直方图的云背景下低帧频小目标探测方法

Dim Target Detection Based on Optical Flow Histgram in Low Frame Frequence in Clouds Background

对低帧频、云层背景下,低信噪比的弱点目标探测率降低的问题,提出了光流直方图(OFH)的定义,并且给出了OFH的性质。分析了低帧频下红外图像探测弱点目标时探测率降低的原因,提出了一种基于OFH背景补偿的红外点目标探测算法。利用OFH得到背景的运动矢量,进行运动背景补偿;然后利用目标与云层运动差异性,得到帧间比较结果,并对比较结果通过Robinson滤波器进一步滤除残留的边缘,达到降低虚警的目的。实验结果表明,该算法可以显著提高在复杂背景下红外点目标检测概率,并且能够探测出信噪比为1的目标。

The detection ratio of dim target with low signal-noise-ratio （SNR） in cloud background especially using low frame frequency detector decreased notably. Optical flow histogram （OPH）, its characters is proposed, and its character is presented. Then the reason of low target detection radio from infrared image using low frame frequency detector is analyzed. And based on this analysis, an algorithm of infrared dim target detection based on background motion compensation is advanced. This algorithm uses OPH to compute the background motion vector, and make background compensation. By distinguishing movement difference between target and background, the comparison result is gained. In order to reduce the false alarm, this result is filtered by Robinson filter to reduce the residues edges. The experimental results have proved that this algorithm can improvegreatly the probability of infrared point target detection, and detect dim targets with SNR of 1.