超谱遥感图像降维方法研究现状与分析

Research and Analysis of Hyperspectral Remote Sensing Image Dimensional Reduction

随着成像光谱仪的发展 ,超谱遥感图像的研究已进入到一个新的阶段———对获取的超谱数据进行有效处理和利用的阶段。目前的处理方法主要集中在对超谱图像的数值分析处理上 ,比如大气校正、降低数据维数、信息提取、分类与压缩等方面。而超谱图像降维方法的研究是做好后继处理的一个关键步骤 ,降维方式的正确选取与使用 ,对于发展和完善那些针对超谱海量数据和丰富信息特点的算法和软件有极大的好处。文章从波段选择、划分数据源、特征提取和融合等 4个角度对目前超谱图像的各种降维方法进行了综合归纳和分析。力图为超谱图像处理寻找突破点 。

With the development of spectrometer, the research of hyperspectral remote sensing image has come into a new stage-processing and utilizing the acquired image efficiently. Now many processing methods are centered on arithmetic analysis processing of hyperspectral, such as atmosphere correction, dimensional reduction, information extraction, classification, compression, and so on. Whereas dimensional reduction of hyperspectral image is an important step to continue subsequent procedure. To select a dimensional reduction method correctly will affects the arithmetic and software which deal with plenty of data and abundant information of hyperspectral image. This paper generalizes and analyzed various methods from the point of view of band selection, subspace decomposition, feature extraction and fusion both at home and abroad.