[1]王立国,马骏宇,李阳.联合多种空间信息的高光谱半监督分类方法[J].哈尔滨工程大学学报,2021,42(2):280-285.[doi:10.11990/jheu.201907019]
 WANG Liguo,MA Junyu,LI Yang.Hyperspectral semi-supervised classification algorithm considering multiple spatial information[J].Journal of Harbin Engineering University,2021,42(2):280-285.[doi:10.11990/jheu.201907019]
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联合多种空间信息的高光谱半监督分类方法(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
42
期数:
2021年2期
页码:
280-285
栏目:
出版日期:
2021-02-05

文章信息/Info

Title:
Hyperspectral semi-supervised classification algorithm considering multiple spatial information
作者:
王立国 马骏宇 李阳
哈尔滨工程大学 信息与通信工程学院, 黑龙江 哈尔滨 150001
Author(s):
WANG Liguo MA Junyu LI Yang
College of Information and Communications Engineering, Harbin Engineering University, Harbin 150001, China
关键词:
空谱联合半监督学习邻域信息高光谱分类Gabor滤波SVM主成分分析
分类号:
TP75
DOI:
10.11990/jheu.201907019
文献标志码:
A
摘要:
高光谱影像分类在遥感学科中具有重要的地位,针对传统高光谱图像分类忽略图像空间特征以及分类过程中有标签样本数目少的问题,本文提出了联合多种空间信息的高光谱半监督分类方法。该方法在高光谱图像处理的各个环节均引入了空间信息。此外,该方法对训练样本集进行扩充时,针对高光谱图像的特点,将教与学算法应用于图像分类中,并且将差分算法与教与学算法结合,平衡了搜索能力与时间复杂度之间的关系。经过实验验证,在有标签样本少的情况下,本文方法相比于经典算法SVM和几种性能优异的算法,在分类性能OA、AA以及Kappa系数上均有提升,证明了本文方法引入空间信息提高分类精度的有效性。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-07-04。
基金项目:国家自然科学基金项目(61675051,62071084).
作者简介:王立国,男,教授,博士生导师.
通讯作者:王立国,E-mail:wangliguo@hrbeu.edu.cn.
更新日期/Last Update: 2021-02-27