| 增强形态学建筑物指数应用于高分辨率影像中建筑物提取 |
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| 引用本文： | 胡荣明,黄小兵,黄远程.增强形态学建筑物指数应用于高分辨率影像中建筑物提取[J].测绘学报,2014,43(5):514-520. |
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| 作者姓名： | 胡荣明 黄小兵 黄远程 |
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| 作者单位： | 西安科技大学 |
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| 基金项目： | 国家自然科学基金(61102112);陕西省教育厅科研计划项目(2013JK0946);测绘遥感信息工程国家重点实验室开放基金(12R04) |
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| 摘 要： | 分辨影像是城市地物覆盖分析的重要数据基础，本文提出了一种增强的形态学建筑物指数（EMBI），利用该指数和地物的几何形状约束来完成高分辨率建筑物的自动提取。本方法首先提取城市的不透水层特征，然后通过建立建筑物属性与形态学运算之间的关系得到了EMBI特征图像以增强对建筑物的描述，随后结合形状特征（长宽比，面积等）采用决策树分析的方法完成对建筑物的最终提取。为了验证本文提出的方法，利用华盛顿商业街的航空高分辨高光谱HYDICE影像和武汉洪山区的两幅QuickBird影像进行实验，实验的精度对比反映本文算法比MBI算法能获得更好的建筑物提取结果，其总体精度分别提高了7.31％，6.48％，7.83％，从而表明EMBI算法更可靠。
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| 关 键 词： | 高分辨率影像 增强形态学建筑物指数 城市不透水层 形状特征 决策树 |
| 收稿时间： | 2013-12-02 |
| 修稿时间： | 2014-02-15 |
An Enhanced Morphological Building Index for Building Extraction from High-Resolution Images |
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| Abstract: | High-resolution images are important basic data for urban surface features coverage analysis. This study proposed an enhanced morphological building index (EMBI) for automatic building extraction from high-resolution remotely sensed imagery. Firstly we extracted the urban impervious feature, and then EMBI was built based on a multi-scale white top-hat morphology reconstruction operation on the feature, which taking advantage of the relationship between the physical properties of buildings and morphological operators. Subsequently, the EMBI feature image combined with the shape characteristics (length-width ratio, area, etc.) completed the final building extraction using a decision tree method. In order to verify the proposed method, the Washington Commercial Street high-resolution hyperspectral HYDICE image and Wuhan Hongshan District two QuickBird images were used. In these experiments, the EMBI algorithm achieved satisfactory results and outperformed the MBI algorithm in terms of accuracies, i.e. the overall accuracy respectively increased by 7.31%, 6.48%, 7.83%, which proved that the EMBI algorithm performed more reliability. |
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