| 基于多源遥感数据融合的SVM分类研究 |
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| 引用本文： | 王友,王双亭,尹鹏飞.基于多源遥感数据融合的SVM分类研究[J].河南城建高等专科学校学报,2013(6):46-50. |
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| 作者姓名： | 王友 王双亭 尹鹏飞 |
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| 作者单位： | 河南理工大学测绘与国土信息工程学院,河南焦作454000 |
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| 摘 要： | 针对SVM对遥感数据进行分类时出现的“同谱异物”和“椒盐现象”,提出利用LiDAR数据和遥感影像相融合的分类方法.实验结果表明：该方法在有效提高分类精度和解决“同谱异物”与“椒盐现象”的同时,还可以加快分类速度.
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| 关 键 词： | 支持向量机 多源遥感 影像融合 遥感分类 |
A Study of SVM classification based on multi-source remote sensing date fusion |
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| WANG You,WANG Shuang-ting,YIN Peng-fei.A Study of SVM classification based on multi-source remote sensing date fusion[J].Journal of Henan Urban Construction Junior College,2013(6):46-50. |
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| Authors: | WANG You WANG Shuang-ting YIN Peng-fei |
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| Affiliation: | (School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China) |
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| Abstract: | The classification method combined with LiDAR data and remote sensing image is proposed in the light of ＂same spectrum with different objects＂ and ＂salt and pepper＂ caused by SVM for classification of re- mote sensing data. The results showed that this method can effectively improve the classification accuracy and resolve the problem of ＂same spectrum with different objects＂ and ＂salt and pepper＂ and can also accelerate the classification speed. |
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| Keywords: | SVM multi-source remote sensing data fusion remote sensing classification |
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