红外与毫米波学报2025，Vol.44Issue(2)：277-288,12.DOI:10.11972/j.issn.1001-9014.2025.02.015
基于张量奇异值部分和与方向残差加权的红外小目标检测算法
Infrared small target detection algorithm via partial sum of the tensor nuclear norm and direction residual weighting
摘要
Abstract
Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small tar-get detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting meth-od(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective back-ground suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in sup-pressing the background and improving the detection ability of the target.关键词
红外弱小目标检测/红外块张量模型/张量核范数的部分和/方向残差加权Key words
infrared small target detection/infrared patch tensor model/partial sum of the tensor nuclear norm/direction residual weighting分类
信息技术与安全科学引用本文复制引用
孙斌,夏星玲,富容国,史亮..基于张量奇异值部分和与方向残差加权的红外小目标检测算法[J].红外与毫米波学报,2025,44(2):277-288,12.基金项目
Supported by the Key Laboratory Fund for Equipment Pre-Research(6142207210202) （6142207210202）
