摘要
提出了一种基于多值免疫网络的多光谱遥感影像分类方法.该方法用选取的训练样本对多值免疫网络进行网络训练,得到具有记忆功能的免疫网络结构,然后利用多值免疫网络对多光谱遥感影像进行分类.实验结果证明,该算法分类精度上优于传统的分类方法,总精度和Kappa系数分别达到了88.84%和0.8605,因而具有实用价值.
In this paper, some initial investigations are conducted to employ multiple-valued immune network （MVIN） for classification of multi-spectral remote sensing image. The proposed method trains the immune network using the samples of regions of interest and obtains the memorial immune network. Image classification task by MVIN is attempted and the preliminary results are provided. The experiment show that the method is superior to traditional algorithms, and its overall accuracy and Kappa coefficient reach 88.84% and 0. 8605 respectively.
出处
《计算机学报》
EI
CSCD
北大核心
2007年第12期2181-2188,共8页
Chinese Journal of Computers
基金
国家"八六三"高技术研究发展计划项目基金(2007AA12Z148)
国家自然科学基金(40471088
40771139)资助~~
关键词
人工免疫系统
遥感
影像分类
模式识别
免疫网络
artificial immune system
remote sensing
image classification
pattern recognition
immune network
