ABSTRACT When using very high-resolution (VHR) remote sensing images acquired at different times to detect building changes, the building positional inconsistencies caused by different satellite imaging angles are an outstanding issue. To tackle this problem, a novel building change detection method based on pseudo-orthorectification (PO) is proposed. First, to determine the building displacement value, a fast line detection method is used to accurately extract the building vertical facade contour lines under the constraint of the Object Space Positioning Consistency (OSPC). Second, the building roof sample selection is automatically conducted under the constraint of building facade contour lines, and the Grab-Cut algorithm is used to extract the roofs combining with corresponding geometric rules. Then, the roof of each building is shifted along the elevation line to its real location. Finally, subtraction is applied to generate the difference image, and reliable change information is obtained by integrating NDVI and shadow information of the building. Three sets of WorldView and QuickBird satellite images are used to compare the proposed method with three state-of-the-art methods. The experimental results show that the average accuracy of the proposed method can reach 92.80%, which is 12.66% higher than that of compared methods.

中文翻译：

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基于伪正射校正的超高分辨率遥感影像建筑物变化检测

摘要 在使用不同时间获取的甚高分辨率（VHR）遥感图像检测建筑物变化时，卫星成像角度不同导致的建筑物位置不一致是一个突出问题。为了解决这个问题，提出了一种基于伪正射校正（PO）的新型建筑物变化检测方法。首先，确定建筑物位移值，采用快速线检测方法，在对象空间定位一致性（OSPC）约束下准确提取建筑物垂直立面轮廓线。其次，在建筑立面轮廓线约束下自动进行建筑屋顶样本选择，结合相应的几何规则使用Grab-Cut算法提取屋顶。然后，每个建筑物的屋顶都沿着立面线移动到其实际位置。最后应用减法生成差分图像，通过整合NDVI和建筑物阴影信息得到可靠的变化信息。三组 WorldView 和 QuickBird 卫星图像用于将所提出的方法与三种最先进的方法进行比较。实验结果表明，所提方法的平均准确率可达92.80%，比对比方法高出12.66%。三组 WorldView 和 QuickBird 卫星图像用于将所提出的方法与三种最先进的方法进行比较。实验结果表明，所提方法的平均准确率可达92.80%，比对比方法高出12.66%。三组 WorldView 和 QuickBird 卫星图像用于将所提出的方法与三种最先进的方法进行比较。实验结果表明，所提方法的平均准确率可达92.80%，比对比方法高出12.66%。