| 应用分水岭变换与支持向量机的极化SAR图像分类 |
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| 引用本文： | 巫兆聪,欧阳群东,胡忠文.应用分水岭变换与支持向量机的极化SAR图像分类[J].武汉大学学报(信息科学版),2012,37(1):7-10,72,127. |
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| 作者姓名： | 巫兆聪 欧阳群东 胡忠文 |
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| 作者单位： | 武汉大学遥感信息工程学院,武汉市珞喻路129号,430079 |
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| 基金项目： | 国家863计划资助项目，国家自然科学基金资助项目，中央高校基本科研业务费专项资金资助项目 |
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| 摘 要： | 结合分水岭变换与支持向量机的特性,提出一种新的极化SAR图像分类算法。其基本思想是先通过分水岭变换及区域合并处理,将极化SAR图像分割成一系列同质区;再以同质区为基本单元,进行特征提取及样本选择后采用支持向量机分类。实验结果表明,该算法可有效降低相干斑对分类的影响,与传统基于像素的SVM算法相比,其分类精度有显著的提高,且结果也更易于理解。
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| 关 键 词： | 极化SAR图像分类 分水岭变换 区域合并处理 支持向量机 |
Polarimetric SAR Image Classification Using Watershed-Transformation and Support Vector Machine |
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| WU Zhaocong,OUYANG Qundong,HU Zhongwen.Polarimetric SAR Image Classification Using Watershed-Transformation and Support Vector Machine[J].Geomatics and Information Science of Wuhan University,2012,37(1):7-10,72,127. |
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| Authors: | WU Zhaocong OUYANG Qundong HU Zhongwen |
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| Institution: | 1(1 School of Remote Sensing and Information Engineering,Wuhan University,129 Luoyu Road,Wuhan 430079,China) |
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| Abstract: | Considering the properties of watershed-transformation and support vector machine,a method for classifying polarimetric SAR image is proposed in this paper.First,polarimetric SAR image is segmented into a series of homogenous regions through watershed transformation and region merging process.Then,region-based classification is performed by utilizing support vector machine after feature extraction and sample selection.Experimental results show that the proposed classification method depresses speckle effectively,when in comparison with traditional pixel-based SVM algorithm,the classification accuracy is improved by dramatically and more interpretable result can also be achieved. |
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| Keywords: | polarimetric SAR image classification watershed transformation region merging process support vector machine |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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