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| 空间邻接支持下的遥感影像分类 | |
| 引用本文： | 乔程,沈占锋,吴宁,胡晓东,骆剑承.空间邻接支持下的遥感影像分类[J].遥感学报,2011,15(1):88-99. |
| 作者姓名： | 乔程 沈占锋 吴宁 胡晓东 骆剑承 |
| 作者单位： | 1. 中国科学院,遥感应用研究所,北京,100101;中国科学院研究生院,北京,100049 2. 中国科学院,遥感应用研究所,北京,100101 3. 浙江大学区域城市规划系,浙江,杭州,310058 |
| 基金项目： | 国家高技术研究发展计划("863"计划)项目，国家自然科学基金 |
| 摘 要： | 传统光谱分类法的局限性促使了遥感“图谱耦合”认知理论的发展, 使其更加注重了空间信息的应用。
然而, 已有的分类方法虽也融入了空间形态、空间关系的应用, 在精度上有一定的提高, 但在空间规律定量描述、
地物实际分布边界跟踪等方面仍存在不足。本文发展了一种空间邻接支持下的遥感影像分类方法: 通过基准地物的
精确提取进而搜索与其邻接的目标地物, 对邻接范围内的地类混淆以及非邻接范围内的目标类误分一并进行修正,
并以近海地物分类为例进行试验, 获得了更为精确、合理的分类结果, 也为后续逐步精确地提取各地物提供了 |
| 关 键 词： | 遥感分类 图谱耦合 空间邻接 分类修正 |
| 收稿时间： | 2010/1/21 0:00:00 |
| 修稿时间： | 2010/10/24 0:00:00 |
Remote sensing image classification method supported by spatial adjacency |
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| QIAO Cheng,SHEN Zhanfeng,WU Ning,HU Xiaodong and LUO Jiancheng.Remote sensing image classification method supported by spatial adjacency[J].Journal of Remote Sensing,2011,15(1):88-99. | |
| Authors: | QIAO Cheng SHEN Zhanfeng WU Ning HU Xiaodong and LUO Jiancheng |
| Institution: | Chinese Academy of Sciences Institute of Remote Sensing Applications, Beijing 100101, China; Chinese Academy of Sciences, Beijing 100049, China;Chinese Academy of Sciences Institute of Remote Sensing Applications, Beijing 100101, China;Zhejiang University Department of Regional Urban Planning, Zhejiang Hangzhou 310058, China;Chinese Academy of Sciences Institute of Remote Sensing Applications, Beijing 100101, China; Chinese Academy of Sciences, Beijing 100049, China;Chinese Academy of Sciences Institute of Remote Sensing Applications, Beijing 100101, China |
| Abstract: | The image classification is a key step for remote sensing data transforming into practical information and knowledge,which has always been the core problem in the remote sensing field.The limitations in traditional spectral classification method otherwise promotes the theory development on the spatial-spectral coupled information cognition of remote sensing,which focuses more on the spatial relationship.However,the current classification revision methods have configured the spatial forms and relationship wh... |
| Keywords: | remote sensing classification spatial-spectral coupled information spatial adjacency classification revision |
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