红外技术2024，Vol.46Issue(3)：305-313,9.
基于稀疏增强重加权与掩码块张量的红外弱小目标检测
Infrared Dim Target Detection Based on Sparse Enhanced Reweighting and Mask Patch-tensor
摘要
Abstract
The high heterogeneity of complex backgrounds destroys the low rank of a scene,and it is difficult for existing algorithms to use low-rank sparse recovery methods to separate dim targets from the background.To resolve this problem,this study transforms the dim target detection problem into a convex optimization function-solving problem for tensor models.It proposes a detection model based on sparsely enhanced reweighting and mask patch tensors.First,the stacked mask patch image was expanded into a tensor space,and a mask patch-tensor model was constructed to filter the candidate targets.Thus,a sparse enhanced reweighting model was constructed using structural tensors to suppress background clutter,and the limitation of setting the weighting parameters can be overcome by solving convex optimization functions.The experiments show that the proposed algorithm outperforms recent representative algorithms regarding the background suppression factor and signal-to-noise ratio gain,demonstrating its effectiveness.关键词
小目标检测/低秩稀疏恢复/掩码块张量/稀疏增强重加权Key words
dim target detection/low rank sparse recovery/mask patch-tensor/sparse enhanced reweighting分类
计算机与自动化引用本文复制引用
孙尚琦,张宝华,李永翔,吕晓琪,谷宇,李建军..基于稀疏增强重加权与掩码块张量的红外弱小目标检测[J].红外技术,2024,46(3):305-313,9.基金项目
国家自然科学基金项目(61841204,61962046,62001255,62066036,62262048) （61841204,61962046,62001255,62066036,62262048）
内蒙古杰青培育项目(2018JQ02) （2018JQ02）
内蒙古科技计划项目(2020GG0315,2021GG0082) （2020GG0315,2021GG0082）
中央引导地方科技发展资金项目(2021ZY0004)) （2021ZY0004）
内蒙古草原英才,内蒙古自治区自然科学基金(2022MS06017,2018MS06018,2019MS06003) （2022MS06017,2018MS06018,2019MS06003）
教育部"春晖计划"合作科研项目(教外司留1383号) （教外司留1383号）
内蒙古自治区高等学校科学技术研究项目(NJZY145)资助. （NJZY145）
