[1]张亚亚,张立民,刘小伟,等. 基于语义网的遥感图像分类[J].计算机技术与发展,2015,25(05):218-223.
　ZHANG Ya-ya,ZHANG Li-min,LIU Xiao-wei,et al. Remote Sensing Image Classification Based on Semantic-net[J].,2015,25(05):218-223.
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 基于语义网的遥感图像分类()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年05期
页码:
218-223
栏目:
应用开发研究
出版日期:
2015-05-10

文章信息/Info

Title:
 Remote Sensing Image Classification Based on Semantic-net
文章编号:
1673-629X（2015)05-0218-06
作者:
 张亚亚; 张立民; 刘小伟; 徐涛
 海军航空工程学院 电子信息工程系
Author(s):
 ZHANG Ya-ya;  ZHANG Li-min ; LIU Xiao-wei;  XU Tao
关键词:
 ; 语义解译; 基于知识; 隶属度函数; InterIMAGE系统; 区域匹配; 遥感图像
Keywords:
 ; semantics interpretation ; knowledge based;  membership functions ; InterIMAGE system;  region match ; remote sensing images
分类号:
TP391
文献标志码:
A
摘要:
 为充分利用遥感图像的先验知识，提高地物信息提取的效率，针对以往低分辨率遥感图像基于像素知识分类出现的问题，提出了一种基于对象的语义网的遥感图像知识分类框架。通过利用语义网络表示地物种类之间的层次关系，研究地物种类的特征属性，通过多种属性集共同描述对象，研究基于模糊隶属度函数的图像对象及其概念的匹配程度，对图像进行精确分类。在InterIMAGE系统中的仿真实验结果表明，通过与人工解译的真值图进行对比，该方法在不需要特定提供样本的情况下，有效提高了地物信息提取的效率和准确度。
Abstract:
 For full use of priori knowledge for remote sensing images to improve the efficiency of land cover information extraction,in view of the problem on low-resolution remote sensing images on pixel knowledge-based classification,present a remote sensing image knowledge classification framework of semantic-net based on the object. Using semantic network to represent the land cover categories hierarchical relationship,research the feature of land cover categories,and by multi-attribute sets to describe the objects,study the matc-hing degree of image objects and concepts based on fuzzy membership function to interpret image. Simulation results on InterIMAGE sys-tem show that the method has improved the efficiency and accuracy in the case of without special samples,compared with the manual in-terpretation of the ground truth image .

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更新日期/Last Update: 2015-07-27