Abstract：Hyperspectral remote sensing information intelligent processing has significant theoretical and practical values to its wide applications. Support Vector Machine, as one effective mean of machine learning, is a potential classification approach to hyperspectral RS because of its suitability for high-dimensional dataset, insufficient samples and uncertainties. But it is necessary to pay more attentions to the following issues based on the characteristics of hyperspectral RS information: multi-class classification strategy, optimization of support vector and feature space, selection and optimization of kernel function and so on. Oriented to the requirements of intelligent information processing, the framework and processing flow of hyperspectral RS Data Mining (HRSDM) is proposed, and the types of discovered knowledge and typical DM modes are discussed.
收稿日期: 2009-03-19
引用本文:
杜培军;陈云浩. 高光谱遥感信息智能处理的若干理论与技术问题[J]. , 2006, 24(0601): 47-51.
;. Some Theoretic and Technical Issues on Hyperspectral Remote Sensing Information Intelligent Processing. , 2006, 24(0601): 47-51.
2006, Vol. 24 
