| 多分类器联合监督分类方法研究 |
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| 引用本文： | 饶雄,高振宇.多分类器联合监督分类方法研究[J].四川测绘,2006,29(1):15-16,14. |
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| 作者姓名： | 饶雄 高振宇 |
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| 作者单位： | 武汉大学遥感信息工程学院 湖北武汉430079 |
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| 摘 要： | 针对遥感图像监督分类方法适用范围不同且分类机制各有优劣的特点,本文提出将最大似然法与最小距离法结合的监督分类法。对eTM 影像进行分类,结果表明,与单一分类器的分类结果相比,分类器结合的监督分类技术能有效提高遥感图像专题信息提取的精度。
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| 关 键 词： | 多分类器 监督分类 主分量分析 |
| 文章编号： | 1001-8379（2006）01-0015-02 |
| 收稿时间： | 2005-09-28 |
| 修稿时间： | 2005-09-28 |
An Approach to the Supervised Classification with Multi-classifier |
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| RAO Xiong,GAO Zhen-yu.An Approach to the Supervised Classification with Multi-classifier[J].Surveying and Mapping of Sichuan,2006,29(1):15-16,14. |
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| Authors: | RAO Xiong GAO Zhen-yu |
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| Institution: | School of Remote Sensing Infomation Engineering, Wuhan University, Wuhan 430079, China |
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| Abstract: | As different Supervised Classification method in Remote Sensing based on different mathematical principle,each method has its own advantages and disadvantages.To try to combine two or even more classifiers and make use of each advantages and supplement each other is efficient to improve the accuracy of classification.Compared to single classifier,the results show the supervised classification method of multi-classifier jointed can improve the accuracy of classification in Remote Sensing. |
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| Keywords: | Multi-classifier Supervised classification |
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