摘要
高光谱图像在高维特征空间中的凸体特性是凸体几何类光谱解混方法的理论依据,这类光谱解混方法具有直观性强、复杂度低、效率高等优点,是高光谱图像光谱解混方法研究的一个重要分支。本文旨在对国内外基于凸体几何理论的光谱解混方法进行回顾,指出这类方法研究中需要特别关注的若干问题,并着重对:①数据降维对凸体几何端元提取方法的影响,②两类经典的单形体体积衡量标准,③3个单形体体积计算公式及其关系3个问题进行简要分析,得到初步分析结果。
Convex geometry theory is the foundation of geometric spectral unmixing approaches in highly dimensional feature space for hyperspectral imagery. It is an important research field of spectral umixing for the geometric methods,and they have the characteristics of intuition,simplicity and high performance. A review of convex geometry-based spectral unmixing methods is summarized,and some primary problems the researchers usually confronted are concluded in the paper. Principally,three main problems are briefly analyzed herein:(1)the influence of Dimensionality Reduction(DR)on the geometric endmember extraction methods for hyperspectral imagery;(2)the difference of two classic simplex volume criterions for spectral unmixing;(3)Three formulas and their relationships for simplex volume calculating of spectral unmixing for the hyperspectral imagery. Finally,some elementary analysis results are obtained in the paper.
作者
许宁
胡玉新
耿修瑞
Xu Ning;Hu Yuxin;Geng Xiurui(Key Laboratory of Technology in Geo-spatial Information Processing and Application System,IECAS,Beijing 100190,China;Institute of Electronics,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《遥感技术与应用》
CSCD
北大核心
2019年第5期1028-1039,共12页
Remote Sensing Technology and Application
基金
“十三五”背景预研项目(105060301)
中国地质调查局地质调查项目(1212011120226)
关键词
凸体几何
端元提取
丰度估计
光谱解混
高光谱数据
Convex geometry
Endmember extraction
Abundance estimation
Spectral unmixing
Hyperspectral imagery
