计算机工程与应用Issue(15)：179-182,192,5.DOI:10.3778/j.issn.1002-8331.1308-0129
基于二叉划分树的多维尺度分析图像分类算法
Multidimensional scaling used for image classification based on binary partition trees
焦斌亮 1范成龙 2王朝晖1
作者信息
- 1. 燕山大学 信息科学与工程学院，河北 秦皇岛 066004
- 2. 河北省特种光纤与光纤传感重点实验室，河北 秦皇岛 066004
- 折叠
摘要
Abstract
A merging criterion used multidimensional scaling on the basis of binary partition trees algorithm has been pro-posed. It builds regional models after an analysis on hyperspectral image, uses multidimensional scaling on the similari-ties of each regional model, reduces dimensions by removing redundant information, determines relevance by association measure on obtained data, and forms a BPT tree structure through regional merging. The pruning function is used to prune this tree structure on classification step. And the experimental conclusion demonstrates that it obtains a better effect for hyperspectral image classification.关键词
高光谱图像分类/区域模型/二叉划分树/多维尺度分析/关联测量Key words
hyperspectral image classification/regional model/binary partition trees/multidimensional scaling/associa-tion measure分类
信息技术与安全科学引用本文复制引用
焦斌亮,范成龙,王朝晖..基于二叉划分树的多维尺度分析图像分类算法[J].计算机工程与应用,2015,(15):179-182,192,5.
