基于局部积加权对比的红外弱小目标检测

针对复杂背景下因像素点噪声及高亮边缘干扰导致的对红外弱小目标检测率低、虚警率高的问题,提出一种基于局部积加权对比的红外弱小目标检测算法.首先,分别计算目标区域与背景区域均值,并得到目标与局部背景的差异性;提出一种局部积加权方法,极大增强了小目标的显著性与抑制背景杂波的能力;其次,采用多尺度算法增强算法的自适应能力;最后...

Infrared dim small target detection based on local product weighted contrast

An infrared dim small target detection algorithm based on local product weighted contrast is proposed for the low detection rateand high false alarm rate of infrared dim small targets in complex backgrounds caused by pixel noise and high-bright edge interference.First, the mean value of the target area and the background area is calculated respectively, and the difference between target and localbackground is obtained. A local product weighting method is proposed, which greatly improves the salience of small targets and thesuppression ability of background clutter. Second, multi-scale algorithm is used to enhance the adaptive ability of the algorithm. Finally,adaptive threshold segmentation is performed on the saliency image to obtain the real target to be detected. Simulation results show thatcompared with the existing algorithms, SCRg and BSF of the proposed algorithm are improved to a certain extent, and still have goodaccuracy and robustness under the complex background and strong noise interference, achieving the purpose of improving the detectionrate and reducing the false alarm rate.