摘要
针对未知环境条件下的高光谱图像目标检测问题进行了研究,提出了一种基于投影的自动目标检测算法。该算法通过构造正交投影算子预先对部分干扰物信息进行削弱,再以无监督的自动目标搜寻方法找到场景中可能的目标物,将图像数据向可能目标物所张成的子空间投影以增强目标物的信息,然后用匹配的方法完成检测。有效减弱了干扰物对目标检测的影响,缩小了目标搜索的范围。应用此算法对实验采集数据进行处理,取得了较好的结果。
Aiming at hyperspectral target detection in the unknown environments, an automatic target detection algorithm based on projection is presented in this paper. Through orthogonal projection, the approach suppresses part of interference information beforehand and finds the potential targets using unsupervised automatic target search method from the data processed before. After that, it projects the data into the subspace spanned by the potential targets to strengthen the target information and extracts the targets with matching method finally. The algorithm effectively lessens the bad effect of interference on target detection and reduces the range of target searching. The experimental data are processed using our method, and the satisfying results are achieved.
出处
《计测技术》
2005年第3期4-7,58,共5页
Metrology & Measurement Technology
基金
国家自然科学基金资助项目(60172037)国防基金资助项目(51401040204HK0359)航空基金资助项目(03D53032)西北工业大学科技创新基金资助项目
关键词
光谱异常
正交投影
自动目标搜寻方法
spectral anomaly
orthogonal projection
automatic target search method