摘要
端元提取是高光谱遥感信息提取与分析的基础,也是解决高光谱图像混合像元分解的关键。本文针对研究区高光谱遥感数据特点,进行了辐射校正、最小噪声分离变换(MNF)及纯净像元指数(PPI)处理,在此基础上,应用二维散点图和三维散点图分别提取了端元波谱,并开展了端元属性的判别研究。岩矿端元的提取与分析为后续岩矿种类识别奠定了基础,直接影响最终成果的准确度。
The end-member extraction is the foundation of the hyperspectral remote sensing information extrac- tion and analysis and is also the key to pixel unmixing. In view of hyperspectral remote sensing data characteris- tics of the study area, the authors carried out the digital image processing of the radiance correction, minimum noise fraction （MNF） and pixel purity index （PPI） and, on such a basis, extracted the end-member spectra by using two-dimensional scatter diagram and three-dimensional scatter diagram, and conducted the research on the discrimination of end-member attributes. The extraction and analysis of rocks and minerals constitute the foun- dation for the recognition of rocks and minerals and directly affect the accuracy of the results.
出处
《岩石矿物学杂志》
CAS
CSCD
北大核心
2013年第2期213-220,共8页
Acta Petrologica et Mineralogica
基金
国家自然科学基金(41102225)
地质灾害防治与地质环境保护国家重点实验室自主课题(SKLGP2011Z013)
关键词
高光谱遥感
端元
最小噪声分离变换
纯净像元指数
hyperspectral remote sensing
end-member
minimum noise fraction （MNF）
pixel purity index （PPI）
