摘要
随着遥感技术的快速发展,遥感图像得到广泛的应用,其中目标检测是遥感图像众多应用中非常重要的一个分支。目前大多数目标检测算法都是基于单时相遥感图像,对于多时相遥感数据的处理方法较少。最近发表的多时相目标检测算法有滤波张量分析,其将多重线性函数与张量相对应的关系应用于遥感图像目标检测,但该算法只能进行单目标检测,无法同时检测多个目标。本文借鉴多目标约束能量最小化算法中对于多个目标输出能量的约束和滤波张量分析中对于应用张量滤波器的思想,提出多目标滤波张量分析算法,能够在多时相遥感数据中实现同时检测多个目标。模拟和真实数据实验结果均表明,该算法可以有效地提高多时相图像中多目标检测精度。
With the rapid development of remote sensing technology,the remote sensing data become valuable in many practical applications.Among them,target detection has always been an important topic.However,most of the target detection algorithms in remote sensing images merely concentrate on single-temporal data,and there are few algorithms for multi-temporal data.In the eld of target detection in multi-temporal remote sensing data,filter tensor analysis(FTA)has achieved great success which outperforms other target detection algorithms for single-temporal data.Yet FTA is designed only for single target detection,which means it can not meet the need for practical applications in circumstances where it has to detect more than one target simultaneously.So,in this paper,a modi ed algorithm for multi-target detection in multi-temporal data has been proposed based on the target constraints in multiple target constrained energy minimization and the tensor filter in FTA.Both the experiment results on simulation data and real remote sensing data from Landsat 8 prove that the algorithm proposed in this paper can effectively detect several targets in multi-temporal data.
作者
席彦新
计璐艳
耿修瑞
XI Yanxin;JI Luyan;GENG Xiurui(Key Laboratory of Technology in Geospatial Information Processing and Application System of CAS,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《中国科学院大学学报(中英文)》
CSCD
北大核心
2021年第4期503-510,共8页
Journal of University of Chinese Academy of Sciences
基金
国防科工局高分重大专项(06-Y20A17-9001-17/18,30-Y20A15-9003-17/18,30-Y20A28-9004-15/17)
国家自然科学基金委重大科研仪器研制项目(41427805)资助。
关键词
多目标检测
多时相
滤波张量分析
约束能量最小化
遥感图像
multi-target detection
multi-temporal
filter tensor analysis
constrained energy minimization
remote sensing data