Automated building extraction from high-resolution satellite imagery in urban areas using structural, contextual, and spectral information
Automated building extraction from high-resolution satellite imagery in urban areas using structural, contextual, and spectral information
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DOI：
10.1155/asp.2005.2196
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发表时间：
2005-08-11
期刊：
影响因子：
--
通讯作者：
Davis, CH
中科院分区：
文献类型：
--
作者：
Jin, XY;Davis, CH
高分辨率卫星图像为建筑物提取提供了重要的新数据源。我们展示了一个综合的战略，确定建筑物在1米分辨率的卫星图像的城市地区。使用结构、上下文和光谱信息提取建筑物。首先，一系列的测地线打开和关闭的操作被用来建立一个微分形态轮廓（xm），提供图像的结构信息。建筑假设的产生和验证，通过形状分析应用于该模型。其次，阴影提取使用的阴影提供可靠的上下文信息来假设相邻建筑物的位置和大小。种子建筑矩形验证和生长在一个精细分割的图像。接下来，使用光谱信息提取明亮的建筑物。对不同信息源的提取结果进行独立提取后进行合并。使用IKONOS卫星图像的哥伦比亚市，密苏里州，城市测试网站上的建筑物提取的性能评估报告。结合结构、背景和光谱信息，提取了72.7%的建筑物区域，质量百分比为58.8%。
High-resolution satellite imagery provides an important new data source for building extraction. We demonstrate an integrated strategy for identifying buildings in 1-meter resolution satellite imagery of urban areas. Buildings are extracted using structural, contextual, and spectral information. First, a series of geodesic opening and closing operations are used to build a differential morphological profile (DMP) that provides image structural information. Building hypotheses are generated and verified through shape analysis applied to the DMP. Second, shadows are extracted using the DMP to provide reliable contextual information to hypothesize position and size of adjacent buildings. Seed building rectangles are verified and grown on a finely segmented image. Next, bright buildings are extracted using spectral information. The extraction results from the different information sources are combined after independent extraction. Performance evaluation of the building extraction on an urban test site using IKONOS satellite imagery of the City of Columbia, Missouri, is reported. With the combination of structural, contextual, and spectral information, 72.7% of the building areas are extracted with a quality percentage 58.8%.