| 辅以纹理特征的高分辨率遥感影像分类 |
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| 引用本文： | 陈启浩,高伟,刘修国.辅以纹理特征的高分辨率遥感影像分类[J].测绘科学,2008,33(1):88-90. |
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| 作者姓名： | 陈启浩 高伟 刘修国 |
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| 作者单位： | 中国地质大学研究生院,武汉,430074;中国地质大学信息工程学院,武汉,430074 |
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| 摘 要： | 为了提高对高分辨率影像的分类精度,通过灰度差矢量法快速提取纹理特征,利用BP神经网络并辅以纹理特征,对一幅江西某地0.2m分辨率的航空影像进行分类。结果显示,对比度纹理特征能较好地反映该影像的纹理信息;对光谱特征不典型、纹理特征明显的人工树林,分类精度可达到90%以上;增加纹理特征后,影像分类的总精度也由55%提高到94%。表明这种结合纹理特征和BP神经网络的分类方法,能提高对高分辨率影像分类的精度。
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| 关 键 词： | 遥感影像分类 高分辨率 纹理分析 灰度差矢量 BP神经网络 |
| 文章编号： | 1009-2307（2008）01-0088-03 |
| 收稿时间： | 2006-10-16 |
| 修稿时间： | 2006年10月16 |
Application of texture feature to classification of high resolution remote sensing image |
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| CHEN Qi-hao,GAO Wei,LIU Xiu-guo.Application of texture feature to classification of high resolution remote sensing image[J].Science of Surveying and Mapping,2008,33(1):88-90. |
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| Authors: | CHEN Qi-hao GAO Wei LIU Xiu-guo |
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| Abstract: | For improving the classification accuracy of high resolution image, by extracting texture feature with gray level difference vector fleetly, an aerial image with 0.2m resolution from Jiangxi is classified by BP neural network with extracted texture feature.The result shows that, the contrast texture feature can describe the texture information of this image commendably; the classification accuracy over 90% for plantation with unrepresentative spectral feature and distinct texture feature; the collective classification accuracy of whole image is increased form 55% to 94% using the texture feature.It’s indicated that the classification accuracy of high resolution image can be improved using the way of combining texture feature with BP neural network. |
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| Keywords: | classification of remote sensing image high resolution texture analysis grey level difference vector BP neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
