...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International journal of remote sensing >Multiple-point simulation-based method for extraction of objects with spatial structure from remotely sensed imagery
【24h】

Multiple-point simulation-based method for extraction of objects with spatial structure from remotely sensed imagery

机译：基于多点模拟的遥感影像空间结构物体提取方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Classification of Combining Spectral information and Spatial information upon Multiple-point statistics (CCSSM) is a method for information extraction that introduces multiple-point simulation (MPS) to increase the classification accuracy of remotely sensed imagery data by incorporating structural information through a training image. This paper focuses on (1) applying CCSSM using a multigrid approach to a Satellite Pour l'Observation de la Terre (SPOT) 5 image, (2) adopting consensus-based fusion to combine two different information sources, the spectral information from supervised classification and spatial structure information from the MPS and (3) analysing the change trend for the accuracy of information extraction and optimizing the proportions in the combination of the two different information sources. We demonstrate that, even if the spectral information from the SPOT 5 image used in the classification results in better classification accuracy, with the introduction of spatial structure information from MPS the accuracy of the information extraction can still be increased significantly.
机译：通过多点统计对光谱信息和空间信息进行组合的分类（CCSSM）是一种信息提取方法，该方法引入了多点模拟（MPS），以通过在训练图像中合并结构信息来提高遥感影像数据的分类精度。本文着重于（1）使用多网格方法将CCSSM应用于地面卫星观测（SPOT）5图像，（2）采用基于共识的融合方法来组合两个不同的信息源，来自监督分类的光谱信息（3）分析变化趋势以提高信息提取的准确性，并优化两种不同信息源的组合比例。我们证明，即使来自分类中使用的SPOT 5图像的光谱信息导致更好的分类准确性，但通过引入MPS中的空间结构信息，信息提取的准确性仍然可以显着提高。

著录项

  • 来源
    《International journal of remote sensing》 |2011年第8期|p.2311-2335|共25页
  • 作者

    YONG GE; HEXIANG BAI;

  • 作者单位

    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences,Beijing 100101, China Department of Earth and Space Science and Engineering, York University, 4700 Keele St., Toronto M3J, 1P3 Canada;

    Graduate University of Chinese Academy of Sciences, Beijing 100049, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号