基于时空域融合滤波的红外运动小目标检测算法

针对红外警戒与跟踪系统中的实时弱小运动目标检测问题．提出了一种基于时空域融合滤波的小目标检测算法。算法在空域上利用形态学Tophat滤波抑制背景增强目标．在时域上通过改进的帧间差分方法增强运动目标，时空域处理结果融合分割后，根据目标运动的连续性和规则性．利用相邻帧中可能目标点之间的位置关系判别目标。算法全面考虑到了运动小目标在时域与空域方面的特性，时空域融合增强后可大大提高目标信噪比。通过实际录取的云层背景飞机目标红外数据检测表明，时空域融合滤波方法能更有效地从复杂背景中检测低信噪比运动小目标，减小虚警率．抗噪声干扰能力强。算法易于硬件实现，能够有效地应用于红外搜索与跟踪系统的实时目标检测中。

Temporal-spatial fusion filtering algorithm for small infrared moving target detection

For the real-time detection of small target in the IRST systems, a temporal-spatial fusion filtering algorithm is proposed. The algorithm suppresses background and enhances targets by morphologic Tophat transform in spatial, and detects moving target by improved frame difference method in temporal. After the fusion image segmentation of the temporal and spatial processing result, the real target can be detected by the relation of the possible target＇s position in adjoining frames on the basis of the target＇s moving continuity and regulation. The algorithm entirely considers the characteristic that the small moving target can be detected in temporal and spatial, it enormously increases the target＇s SNR after the temporalspatial fusion enhancement. The detecting results of the true airplane＇s infrared image sequences in cloud background show that the algorithm can be more effective to detect low SNR moving small targets in complex background and reduce false alarm. The algorithm is easy to realize in hardware and can be applied effectively in the real-time target detection of the IRST systems.