计算机技术与发展2012，Vol.22Issue(6)：198-202,5.
基于决策树的高光谱遥感影像分类方法研究
Research on Method of Hyperspectral Remote Sensing Image Classification Based on Decision Tree
摘要
Abstract
In order to validate the feasibility of using decision tree algorithm for hyperspectral remote sensing image classification,it proposes a method of building decision tree automatically for hyperspectral remote sensing image classification. Based on hyperspeclral remote sensing image on-site sampling,sample statistics and training,generate a binary decision tree,extract classification rule from the decision tree and classify the hyperspectral remote sensing image. The whole tree is simple and the classification rules are easy to understand. Both classification efficiency and accuracy are satisfactory. The study makes it "integration" and "automation* to reduce the dimensionality of hyperspectral data,sample selection,sample training,decision tree generation and image classification.关键词
二叉决策树/高光谱遥感影像/分类/最佳阈值/自动构建Key words
binary decision tree/hyperspectral remote sensing image/classification/best threshold/automatic building分类
信息技术与安全科学引用本文复制引用
华晔,张涛,奚后玮,王玉斐,黄秀丽..基于决策树的高光谱遥感影像分类方法研究[J].计算机技术与发展,2012,22(6):198-202,5.基金项目
国家电网科技项目(SG11075-1) （SG11075-1）
