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.