National and Local Joint Engineering Research Center of Space Optoelectronics Technology, Changchun University of Science and Technology, Changchun 130022, China.
Sensors (Basel). 2023 Jul 7;23(13):6215. doi: 10.3390/s23136215.
Infrared small-target enhancement in complex contexts is one of the key technologies for infrared search and tracking systems. The effect of enhancement directly determines the reliability of the monitoring equipment. To address the problem of the low signal-to-noise ratio of small infrared moving targets in complex backgrounds and the poor effect of traditional enhancement algorithms, an accurate enhancement method for small infrared moving targets based on two-channel information is proposed. For a single frame, a modified curvature filter is used in the A channel to weaken the background while an improved PM model is used to enhance the target, and a modified band-pass filter is used in the B channel for coarse enhancement followed by a local contrast algorithm for fine enhancement, based on which a weighted superposition algorithm is used to extract a single-frame candidate target. The results of the experimental data analysis prove that the method has a good enhancement effect and robustness for small IR motion target enhancement in complex backgrounds, and it outperforms other advanced algorithms by about 43.7% in ROC.
复杂背景下的红外小目标增强是红外搜索跟踪系统的关键技术之一。增强效果直接决定了监控设备的可靠性。针对复杂背景下小红外运动目标信噪比低、传统增强算法效果差的问题，提出了一种基于双通道信息的小红外运动目标准确增强方法。对于单帧图像，在 A 通道中使用改进的曲率滤波器来削弱背景，同时使用改进的 PM 模型来增强目标，在 B 通道中使用改进的带通滤波器进行粗增强，然后使用局部对比度算法进行细增强，在此基础上使用加权叠加算法提取单帧候选目标。实验数据分析结果证明，该方法对复杂背景下的小红外运动目标增强具有良好的增强效果和鲁棒性，在 ROC 上比其他先进算法提高了约 43.7%。
