提出了一种自适应滤波的红外小目标检测算法, 该方法由背景去除与目标提取两层二维最小均方滤波器构成.分别引入背景模板与目标模板, 结合二维最小均方滤波方法对原始红外图像进行处理, 有效地剔除了背景噪声与杂波, 同时尽可能地保留了目标信息.在算法实现过程中, 提出了一种步长自动调整算法, 通过图像的统计参数自适应调整步长的大小, 可迭代出TDLMS滤波器的最优权值, 再与权重模板相融合, 有效增强了目标的检测效果.实验结果表明, 该方法能够适应不同背景下的目标检测, 有效提高了红外小目标的检测性能.

An infrared small target detection algorithm based on adaptive filter is proposed, which consists of twolayer Two Dimensional Least Mean Square Filter (TDLMS) filters: background removal and target extraction. The background template and target template are introduced, and the original infrared image is processed by TDLMS filtering method. The background noise and clutter are eliminated effectively, while the target information is preserved as much as possible. In the implementation of TDLMS algorithm, an automatic stepsize adjustment algorithm is proposed. The optimal weights of TDLMS filters can be iterated by adjusting the adaptive stepsize through the statistical parameters of the image, and then fused with the weight template, which effectively enhances the detection effect of the target. The experimental results show that the method can adapt to target detection under different background, and effectively improve the detection performance of small infrared targets.