Research on infrared dim and small target detection algorithm based on local contrast and gradient

The rapid development of infrared technology makes it widely applicable in such fields as military, medical, testing and communications.This paper proposes an algorithm based on local contrast and gradient (LCG). Specifically, the algorithm uses the difference of gaussian and threshold segmentation to preprocess to obtain the position of possible target points. Then, local contrast processing is conducted for the possible target points. Finally, the global is processed using an improved directional gradient. According to the experimental results, the proposed algorithm outperforms the existing algorithms in terms of detection probability and false detection probability.

红外技术的飞速发展使其在军事、医疗、检测及通信等诸多领域得到了广泛应用。本文提出了一种基于局部对比度与梯度的算法（Local Contrast and Gradient，简称LCG）。具体而言，该算法采用高斯差分与阈值分割进行预处理，以获取潜在目标点的位置；随后针对上述潜在目标点开展局部对比度处理；最后利用改进的方向梯度算法对全局图像进行处理。经实验验证，所提算法在检测概率与误检概率两项指标上均优于现有算法。