| 改进的P-SVM支持向量机与遥感数据分类 |
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| 引用本文： | 张睿,马建文. 改进的P-SVM支持向量机与遥感数据分类[J]. 遥感学报, 2009, 13(3): 445-457 |
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| 作者姓名： | 张睿 马建文 |
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| 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 |
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| 基金项目： | 中国科学院知识创新工程重要方向项目(编号：kzcx2-yw-313)和“863”计划项目(编号：2007AA12Z157) |
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| 摘 要： | 本文介绍了将P-SVM算法引入多光谱/高分辨率遥感数据的分类, 并且展示了卫星ASTER和航空ADS40数字影像分类的技术过程和结果验证。结果表明：P-SVM方法的分类精度不低于SVM, 并减少了时耗。
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| 关 键 词： | SVM P-SVM 多光谱/高分辨率遥感数据 遥感数据分类 |
| 收稿时间： | 2007-09-19 |
| 修稿时间： | 2007-11-13 |
Improved support vector machine and classification for remotely sensed data |
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| ZHANG Rui and MA Jian-wen. Improved support vector machine and classification for remotely sensed data[J]. Journal of Remote Sensing, 2009, 13(3): 445-457 |
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| Authors: | ZHANG Rui and MA Jian-wen |
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| Affiliation: | 1. Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China; 2. Graduate University, Chinese Academy of Sciences, Beijing 100049, China;1. Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China |
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| Abstract: | In this paper, the P-SVM algorithm was introduced into multi-spectral/high-spatial resolution remotely sensed data classification and it is applied to classification of ASTER satellite data and ADS40 aerial digital data. The experiments indicate that the P-SVM is at least competitive with the standard SVM algorithm in classification accuracy of remotely sensed data and the time needed is less. |
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| Keywords: | SVM P-SVM multi-spectral/high-spatial resolution remotely sensed data classification |
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