| 基于PCA-BPNN的多光谱遥感影像分类 |
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| 引用本文： | 吴芳,贾永红.基于PCA-BPNN的多光谱遥感影像分类[J].地理空间信息,2006,4(1):15-17. |
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| 作者姓名： | 吴芳 贾永红 |
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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： | 基于BP算法的神经网络方法目前已广泛运用于遥感影像分类,提出一种主成分分析(PCA)与BP神经网络相结合的遥感影像分类方法——PCA-BPNN,实验证明该方法是可行并且有效的,在减少计算量和加快收敛的同时,提高了分类的精度。
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| 关 键 词： | BP神经网络 影像分类 主成分分析 |
| 文章编号： | 1672-4623（2006）01-0015-03 |
| 收稿时间： | 2005-03-28 |
| 修稿时间： | 2005年3月28日 |
Classification of Multispectral Remote Sensing Image Based On PCA-BPNN |
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| WU Fang,JIA YongHong.Classification of Multispectral Remote Sensing Image Based On PCA-BPNN[J].Geospatial Information,2006,4(1):15-17. |
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| Authors: | WU Fang JIA YongHong |
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| Institution: | School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China |
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| Abstract: | A neural network based on back propagation has been widely used in the classification of remote sensing images. In this paper, PCA-BPNN is proposed for classification of multispectral remote sesing images, which combines principal component analysis with BP neural networks. The experiment results demonstrate its feasibility and it can cut down training time and improve the accuracy. |
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| Keywords: | BP neural network image classification principal component analysis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
