基于信息散度特征的高光谱影像识别技术

Target recognition for hyperspectral image based on SID spectral feature

高光谱遥感将确定地物性质的光谱与确定地物空间和几何特性的图像有机地结合在一起。从空间对地观测的角度来说,高光谱遥感信息无论对地物理化特性的深层探索,还是对地物间微小差异的精细识别,以及对自然界的知识发现,都为人类提供了前所未有的丰富信息。其高光谱图像立方体图谱合一的特点,要求人们从光谱维去理解地物在空间维的变化,对二维空间图像的处理与分析需要转化成对每个像元所提取出的光谱曲线的处理与分析。本文提出了一种基于光谱信息散度的高光谱匹配识别算法,并对PHI数据进行了实验分析,验证了算法的有效性。

Hyperspectral remote sensing effectively make the spectral feature and geometric characters of objects together. From the view of earth observation from space,hyperspectral data provide human being more abundant information, not only in the deep explorations of object's physical and chemical characters, but also in the precise classification of different objects and knowledge innovation. Aiming at the hyperspectral image cube, the understanding and data processing in image spatial dimension must be changed to that completed in the spectral dimension. A target recognition algorithm for hyperspectral image based on SID spectral feature has been developed. Experiments of PHI hyperspectral image classification are practiced by using SID matching model.