针对空中红外点目标的特性,提出了一种检测算法.首先,对图像进行高通滤波预处理,增强目标与背景的对比度.增强后的相邻帧图像做差分运算以进行目标的粗检测,提取出候选目标区域;其次,对原图像或预处理后的图像在候选区域内进行自适应分割,检测出点目标;最后,根据目标像素在序列图像中运动的连续性排除噪声干扰,从而准确地检测出真实目标.通过对红外图像序列进行实验,证实了算法的有效性.

According to the features of infrared point target in the sky, a detection algorithm is presented. Firstly, contrast of the images are enhanced by high-pass filter, and then the coarse detection is performed based on differentiating two neighboring frames in image sequence to extract candidate target regions. Secondly, the original image or the enhanced image is segmented in the candidate regions, so the possible point targets are detected. Finally, the true target can be accurately detected by removing noise interference based on continuity of moving target in the image sequence. The effectiveness of the algorithm is proved by the experimental results for several real infrared image sequences.