Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.
IEEE Transactions on Cybernetics(2019)
摘要
In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial ...
更多查看译文
关键词
Feature extraction,Hyperspectral imaging,Manifolds,Sparse matrices,Laplace equations
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络