A split-and-merge technique for automated reconstruction of roof planes
A split-and-merge technique for automated reconstruction of roof planes
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DOI：
10.14358/pers.71.7.855
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发表时间：
2005-07-01
影响因子：
1.3
通讯作者：
King, B
中科院分区：
文献类型：
--
作者：
Khoshelham, K;Li, ZL;King, B
从不同的数据源自动重建建筑物一直是摄影测量和计算机视觉中最具挑战性的问题之一。用于自动建筑物重建的系统在许多情况下由于数据中涉及的复杂性而失败，包括图像噪声、遮挡、阴影和低对比度，以及高度数据的低精度或密度。本文讨论了航空影像分割中的杂草丛生和杂草丛生问题，提出了一种利用高程数据进行分割合并的方法，克服了这一问题。该技术是基于分裂的图像区域，其相关的高度点不落在一个单一的平面，并合并共面的相邻区域。一个强大的平面拟合方法是用来拟合平面表面的高度点，是严重污染的粗差。通过检查它们在形态学上打开的DSM上的斜率和高度，从图像平面区域中提取最终屋顶平面。进行了实验评估，其结果表明，所提出的技术在分裂过度生长的区域，合并欠生长的共面区域，并选择最终的屋顶平面的能力。此外，该方法被证明是计算效率高，重建的屋顶平面是可以接受的精度。
Automated reconstruction of buildings from different data sources has been one of the most challenging problems in photogrammetry and computer vision. Systems for automated building reconstruction fail in many cases due to complexities involved in the data including image noise, occlusion, shadow, and low contrast, as well as, low accuracy or density of height data. In this paper, the problem of overgrown and undergrown regions in the segmentation of aerial images is discussed, and a split-and-merge technique is presented to overcome this problem by making use of height data. This technique is based on splitting image regions whose associated height points do not fall in a single plane, and merging coplanar neighboring regions. A robust plane-fitting method is used to fit planar surfaces to height points that are highly contaminated by gross errors. Final roof planes are extracted out of the image planar regions by checking their slope and height over a morphologically opened DSM. An experimental evaluation is conducted, and its results indicate the capability of the proposed technique in splitting overgrown regions, merging undergrown coplanar regions, and selecting the final roof planes. Also, the method is shown to be computationally efficient, and the reconstructed roof planes are of acceptable accuracy.