基于FACET滤波加权局部对比度的红外小目标检测  

Infrared Small Target Detection Based on FACET Filtering Weighted Local Contrast

作　　者：马鹏阁[1] 王招鹏 王江南 钱金旺 孙俊灵[1] MA Pengge;WANG Zhaopeng;WANG Jiangnan;QIAN Jinwang;SUN Junling(School of Electronics and Information,Zhengzhou University of Aeronautics,Zhengzhou 450000,China)

机构地区：[1]郑州航空工业管理学院电子信息学院,郑州450000

出　　处：《电光与控制》2024年第12期27-32,共6页Electronics Optics & Control

基　　金：国家自然科学基金民航联合基金重点项目(U1833203);航空科学基金(2020Z019055001);河南省科技攻关项目(222102210136)。

摘　　要：针对低空复杂背景下红外图像中目标与背景对比度低、边缘高亮的问题,提出一种基于FACET滤波加权局部对比度的红外小目标检测算法。首先,通过FACET滤波运算获取目标候选像素;然后,利用目标区域和背景区域灰度差异的比率计算局部对比度,同时基于目标和背景的异质性设计了一种加权函数,用来增强目标显著性和抑制背景;最后,通过自适应阈值分割提取真实的目标。在5组真实红外小目标图像数据集上与不同的算法进行性能比较分析,实验结果表明,提出的算法在不同低空复杂场景中具有较好的检测性能。A infrared small target detection method based on FACET filtering weighted local contrast is proposed to address the problem of low contrast between targets and background and high edge brightness in infrared images under low altitude and complex backgrounds.Firstly,the target candidate pixels are obtained through FACET filtering operation.Then,local contrast is calculated by the ratio of grayscale differences between the target and background regions,and a weighted function is designed based on the heterogeneity of the target and background to enhance target saliency and suppress background.Finally,the real target is extracted through adaptive threshold segmentation.The performance of the algorithm is compared and analyzed with different algorithms on five sets of real infrared small target image datasets.The experimental results show that the algorithm proposed has good detection performance in different low altitude complex scenes.

关 键 词：红外小目标 FACET滤波 局部对比度 加权函数 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]