一种新的空时域滤波小目标检测方法

Infrared Small Target Detection Based on Newly Spatial-Temporal Filtering

为了提高红外图像序列中弱小目标的信噪比和检测概率,同时考虑检测算法实时性,提出了一种新的基于空时域滤波的小目标检测方法。首先,以第一帧图像为参考帧,对各帧图像进行运动补偿;然后,对运动补偿后的各帧图像在空域进行方差加权信息熵滤波,对空域滤波后图像采取双向隔帧差分的时域滤波;最后通过检测差分图像中的"凸包",抑制背景和噪声,检测小目标。文中给出了实验结果与分析,并与其他方法作了比较。实验结果表明,上述方法能大幅度的提高目标的信噪比,检测小目标,且实时性好。

To improve the Signal-to-noise Ratio （SNR） and detecting probability of small target in infrared image sequences, a novel method of target detection based on spatial-temporal filtering is proposed. This method considered the real-time characteristic of the detecting algorithm. Firstly, the first frame was set as a reference frame and the other frames were compensated in motion. Secondly, the frames compensated were filtered by variance Weighted Information Entropy （Variance WIE） filter in spatial domain. After that, a bi-directional inter-frame difference method was adopted in temporal domain. At last, by detecting the protruding spot of the difference images, the background and noises in infrared images were inhibited and the small target was detected. The experimental results were analyzed and compared with some other methods. The results show that this approach can highly improve the SNR of target, precisely detect the small infrared target, and express fine real-time performance.