研究复杂背景下弱小目标检测问题对提高靶场光电设备探测能力具有重要意义。根据红外图像的背景复杂程度, 提出一种自适应高斯高通滤波算法。该算法利用改进中值滤波器对图像进行降噪, 采用图像方差加权熵,定量描述红外图像背景复杂程度, 根据图像背景复杂程度自动调整滤波器截止频率, 实现不同背景下红外弱小目标自动检测, 并利用靶场实测光电图像对算法进行了验证。实验结果表明该算法能够有效地在不同图像背景下检测到弱小目标。

Detection of small, low contrast infrared targets in complex backgrounds requires a significant improvement in the detective ability of photoelectric theodolites. An adaptive Gaussian high-pass filter was proposed based on a description of the dagree of infrared background complexity. The noise of images was reduced by updating a medial filter, and the degree of background complexity was quantitatively described by variance-weighted information entropy. The cutoff frequency of the filter was automatically adjusted according to the degree of background complexity.This technique resulted in the automatic detection of small, low contrast targets in different infrared backgrounds. The new method was verified by experiment and the result shows the new method can effectively detect small, low contrast targets in different infrared backgrounds.