| 基于支持向量机的遥感图像分类研究综述 |
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| 引用本文： | 王振武,孙佳骏,于忠义,卜异亚.基于支持向量机的遥感图像分类研究综述[J].计算机科学,2016,43(9):11-17, 31. |
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| 作者姓名： | 王振武 孙佳骏 于忠义 卜异亚 |
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| 作者单位： | 中国矿业大学北京机电与信息工程学院 北京100083,中国矿业大学北京机电与信息工程学院 北京100083,中国矿业大学北京机电与信息工程学院 北京100083,中国矿业大学北京机电与信息工程学院 北京100083 |
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| 基金项目： | 本文受国家高技术研究发展计划(863)重大专项:全球巨型成矿带重要矿产资源与能源遥感探测与评价系统研发(2012AA12A308),核设施退役及放射性废物治理科研项目(FZ1402-08),北京市高校青年英才计划,中国矿业大学(北京)大学生创新计划重点项目资助 |
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| 摘 要： | 遥感技术是目前用于研究地球矿产资源与能源的重要技术手段,遥感图像分类在遥感技术应用中起着关键作用。支持向量机(Support Vector Machines,SVM)是基于VC维(Vapnik-Chervonenkis Dimension)理论和结构风险最小化原理的机器学习方法,已被广泛应用于实际的遥感影像分类中。 对 国内外学者对此做的大量研究 成果进行了系统的总结。对基于支持向量机的遥感图像分类方法进行了层次性梳理,不但纵向分析和比较了每类方法的原理及优缺点,而且对各类方法进行了横向比较和分析,较为系统和完整地概括了基于支持向量机的遥感影像分类方法的研究现状。最后指出了支持向量机算法应用于遥感图像分类的未来发展方向。
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| 关 键 词： | 遥感图像 分类 支持向量机 |
| 收稿时间： | 8/6/2015 12:00:00 AM |
| 修稿时间： | 2015/11/27 0:00:00 |
Review of Remote Sensing Image Classification Based on Support Vector Machine |
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| Affiliation: | School of Mechanical Electronic & Information Engineering,China University of Mining and TechnologyBeijing,Beijing 100083,China,School of Mechanical Electronic & Information Engineering,China University of Mining and TechnologyBeijing,Beijing 100083,China,School of Mechanical Electronic & Information Engineering,China University of Mining and TechnologyBeijing,Beijing 100083,China and School of Mechanical Electronic & Information Engineering,China University of Mining and TechnologyBeijing,Beijing 100083,China |
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| Abstract: | Remote sensing technology is an important technology of studying the earth mineral resources and energy.Remote sensing image classification plays a key role in the application of remote sensing technology.Support vector machine(SVM) is a machine learning method based on VC dimension(Vapnik-Chervonenkis Dimension) theory and structural risk minimization principle,which has been widely used in the actual remote sensing image classification.Domestic and foreign scholars have done a lot of research about it and these studies were systematically summarized in this paper.The remote sensing image classification methods based on the support vector machine is reviewed hierarchically,that is,the principle and characteristics of each method were analyzed and compared laterally and vertically.The research status of the remote sensing image classification based on the support vector machine was summarized systematically and completely in this paper.Finally,the future development direction of support vector machine algorithm applied in the remote sensing image classification was pointed out. |
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| Keywords: | Remote sensing images Classification Support vector machine (SVM) |
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