多尺度匹配的红外变分辨率弱小目标检测

Infrared variable resolution dim target detection with multi-scale matching

针对云层背景下红外变分辨率小目标的成像特性,提出一种基于尺度空间理论的红外弱小目标检测方法。首先建立高斯小目标参数模型,以高斯核生成待检测图像的尺度空间,进而对尺度空间进行最佳尺度匹配,提取目标感兴趣区域(ROI)。然后构造ROI尺度自适应对比度作为检测判据,剔除虚警,实现小目标最终检测。实验结果显示,算法不仅能够准确检测目标,且可以估计目标像尺寸,同时具有较高的检测概率和执行效率。可有效地实现对变分辨率弱小目标的检测。

According to the imaging characteristics of infrared variable resolution dim target in cloudy background, a method for small target detection based on scale space theory was proposed in this paper. Firstly, a Gaussian parameter model was established for small target, and then the scale space of the detected image was generated by using Gaussian kernel. Next, with optimal scale matching for scale space, the target region of interest （ROI） was extracted. Finally, the scale adaptive contrast （SAC） of ROI was calculated as detection criterion to remove the false alarms, achieving small target detection. The results of experiments show that the method proposed in this paper can not only accurately detect the target, but also estimate the size of target, and has high detection rate and efficiency.