摘要
通过对端元概念的引申,提出了更具一般性的特征端元的概念,从而将端元方法的适用范围从高光谱数据拓展到了多光谱数据和全色遥感数据。同时改进了端元提取算法,并提出了基于特征端元提取的像元分解方法。实验结果表明,基于特征端元提取的混合像元分解方法可以得到较好的像元分解结果,并且该方法与传统的端元概念及混合像元分解结果具有良好的可比性。
In this paper, a new and more general concept named ＂feature endmember＂ is presented to extend the concept of ＂endmember＂ for applying the endmember method not only to hyperspectral and multispectral data, but even also to panchromatic data. Furthermore, the algorithm for extracting endmember is improved, and a method for pixel unmixing based on feature endmember extraction is proposed. Some experimental results show that the proposed methodology can be successfully used for decomposition of mixed pixels of hyperspectral data and other remote sensing data and can be comparable with the traditional algorithms.
出处
《高技术通讯》
EI
CAS
CSCD
北大核心
2008年第10期1035-1040,共6页
Chinese High Technology Letters
基金
教育部科技创新工程重大项目培育资金(706004)
国家自然科学基金(60472029)资助项目
关键词
特征端元
像元分解
谱聚类
feature endmember, pixel unmixing, spectral clustering
