Remote sensing image classification method based on evidence theory and decision tree
文献类型：会议论文
| 作者 | Li,Xuerong ; Xing,Qianguo ; Kang,Lingyan |
| 出版日期 | 2010 |
| 会议日期 | 2010-10-13 |
| 会议地点 | . |
| 关键词 | Bayesian Networks Decision Trees Image Analysis Image Classification Image Reconstruction |
| 通讯作者 | Li,X. |
| 英文摘要 | Remote sensing image classification is an important and complex problem. Conventional remote sensing image classification methods are mostly based on Bayesian subjective probability theory, but there are many defects for its uncertainty. This paper firstly introduces evidence theory and decision tree method. Then it emphatically introduces the function of support degree that evidence theory is used on pattern recognition. Combining the D-S evidence theory with the decision tree algorithm, a D-S evidence theory decision tree method is proposed, where the support degree function is the tie. The method is used to classify the classes, such as water, urban land and green land with the exclusive spectral feature parameters as input values, and produce three classification images of support degree. Then proper threshold value is chosen and according image is handled with the method of binarization. Then overlay handling is done with these images according to the type of classifications, finally the initial result is obtained. Then further accuracy assessment will be done. If initial classification accuracy is unfit for the requirement, reclassification for images with support degree of less than threshold is conducted until final classification meets the accuracy requirements. Compared to Bayesian classification, main advantages of this method are that it can perform reclassification and reach a very high accuracy. This method is finally used to classify the land use of Yantai Economic and Technological Development Zone to four classes such as urban land, green land and water, and effectively support the classification. © 2010 Copyright SPIE - The International Society for Optical Engineering. |
| 产权排序 | (1) Graduate University, Chinese Academy of Sciences, Beijing 100080, China; (2) Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, 17 Chunhui Road, Laishan District, Yantai 264003, China |
| 会议录 | Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications III
 |
| 会议录出版者 | SPIE, P.O. Box 10, Bellingham, WA 98227-0010, United States |
| 学科主题 | 摄影测量与遥感 |
| 语种 | 英语 |
| URL标识 | 查看原文 |
| ISSN号 | ISSN:0277786X |
| 源URL | [http://ir.yic.ac.cn/handle/133337/4794]  |
| 专题 | 烟台海岸带研究所_支撑部门 |
| 推荐引用方式 GB/T 7714 | Li,Xuerong,Xing,Qianguo,Kang,Lingyan. Remote sensing image classification method based on evidence theory and decision tree[C]. 见:. .. 2010-10-13. |
入库方式： OAI收割
来源：烟台海岸带研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。