| 粗糙集理论在遥感影像分割中的应用 |
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| 引用本文： | 邵锐,巫兆聪,钟世明.粗糙集理论在遥感影像分割中的应用[J].地理空间信息,2005,3(5):26-28. |
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| 作者姓名： | 邵锐 巫兆聪 钟世明 |
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| 作者单位： | 1. 武汉大学,遥感信息工程学院,湖北,武汉,430079
2. 中国科学院,测量与地球物理研究所,湖北,武汉,430077 |
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| 摘 要： | 结合粗糙集理论和K—均值聚类算法,提出一种遥感影像的粗糙聚类分割方法。根据遥感影像中特征属性的相互依赖关系,应用粗糙集理论的等价关系,求出K—均值聚类所需要的初始类的个数和均值,然后采用聚类算法对图像进行分割。实验结果表明该方法比随机选取聚类的中心点和个数减少了运算量,提高了分类精度和准确性。
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| 关 键 词： | 遥感影像 粗糙集 聚类 粗糙聚类分割 |
| 文章编号： | 1672-4623（2005）05-0026-03 |
| 收稿时间： | 2004-10-29 |
| 修稿时间： | 2004年10月29 |
Application of Rough Sets Theory to Remote Sensing Image Segmentation |
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| SHAO Rui,WU Zhaocong,ZHONG Shiming.Application of Rough Sets Theory to Remote Sensing Image Segmentation[J].Geospatial Information,2005,3(5):26-28. |
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| Authors: | SHAO Rui WU Zhaocong ZHONG Shiming |
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| Institution: | 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China; 2. Institute of Geodesy and Geophysics, Chinese Academy of Sciences,Wuhan 430077, China |
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| Abstract: | This paper presents a remote sensing image segmentation method based on rough set theory and K-means clustering. Using equivalence relations of attributes of remote sensing image, rough set theory offers the number and the centroids of the clusters, which initialize the K-means clustering. And then the image is segmented by K-means clustering algorithm. Compared with the process beginning by random selection of objects as the centroids of the clusters, the computational time requirement is significantly small, the possibility of mistakes in segmentation is reduced and the classification precision and accuracy is improved. |
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| Keywords: | remote sensing image rough sets cluster segmentation using methods of rough sets and cluster |
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