非监督高光谱图像实时目标探测方法研究

项目名称： 非监督高光谱图像实时目标探测方法研究

项目编号： No.61201415

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电子学与信息系统

项目作者： 刘春红

作者单位： 中国农业大学

项目金额： 24万元

中文摘要： 本项目的目的是设计和发展非监督高光谱实时目标探测处理方法。从高光谱实时目标探测的机理出发，利用统计信息学的方法，研究在非监督情况下，如何将RXD方法进行因果化，从而具有实时探测目标能力的问题，利用有效光谱维数方法（ESD）解决RXD方法中阈值分割的问题；研究利用ATGP实时寻找高光谱图像中目标像元的问题；研究将PPI进行因果化，从而具有实时探测目标的问题。在非监督实时目标探测的基础上，研究如何对CEM、TCIMF和LCMV等目标探测方法进行因果化，采用woodbury准则对CEM、TCIMF和LCMV等算法中存在的自相关矩阵实时更新方法进行推导，从而解决自相关矩阵的实时更新速度慢的问题。本项目用接收特征操作曲线对实时化前后的各种算法进行比较。本项目旨在不失时机地开展基于高光谱成像技术的实时目标探测方法研究，逐步形成集"原理－算法－结果评价"于一体的非监督高光谱图像实时目标探测体系。

中文关键词： 高光谱；实时；目标探测；；

英文摘要： The proposed project is to design and develop real-time processing algorithms for Unsupervised Hyperspectral Target Detection (UHTD). Due to the nature of UHTD, in order for UHTD to be effective, the process must be carried in real time such as applications of reconnaissance and surveillance. However, real time processing requires causality in the sense that the process can only use the information available up to the data sample currently being visited. Interestingly, very little work has been investigated to address this issue. The project is based on the mechanism of hyperspectral real-time target detection, by using statistics information methods, under unsupervised condition , proceeding research of the problems how to get causal RXD to let it has real-time target detection ability. Using effective spectral dimension（ESD） to solve the threshold segmentation problems exist in RXD method. Research of using ATGP to searching target pixel specrtral in hyperspectral image. Research of causal PPI to let it has the ability of real-time target detection. Based on unsupervised real-time target detection, research of how to get CEM、TCIMF and LCMV causalized, using woodbury standards to deduct autocorrelation matrix in CEM、TCIMF and LCMV to solve the problem that the autocorrelation matrix update too slowly. The proj

英文关键词： Hyperspectral；real time；target detection；；