首页> 外文期刊>Journal of Geographic Information System >Disparity-Based Generation of Line-of-Sight DSM for Image-Elevation Co-Registration to Support Building Detection in Off-Nadir VHR Satellite Images
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Disparity-Based Generation of Line-of-Sight DSM for Image-Elevation Co-Registration to Support Building Detection in Off-Nadir VHR Satellite Images

机译:基于视差的视线DSM的图像高程共配准生成,以支持离天底VHR卫星图像中的建筑物检测

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The integration of optical images and elevation data is of great importance for 3D-assisted mapping applications. Very high resolution (VHR) satellite images provide ideal geo-data for mapping building information. Since buildings are inherently elevated objects, these images need to be co-registered with their elevation data for reliable building detection results. However, accurate co-registration is extremely difficult for off-nadir VHR images acquired over dense urban areas. Therefore, this research proposes a Disparity-Based Elevation Co-Registration (DECR) method for generating a Line-of-Sight Digital Surface Model (LoS-DSM) to efficiently achieve image-elevation data co-registration with pixel-level accuracy. Relative to the traditional photogrammetric approach, the RMSE value of the derived elevations is found to be less than 2 pixels. The applicability of the DECR method is demonstrated through elevation-based building detection (EBD) in a challenging dense urban area. The quality of the detection result is found to be more than 90%. Additionally, the detected objects were geo-referenced successfully to their correct ground locations to allow direct integration with other maps. In comparison to the original LoS-DSM development algorithm, the DECR algorithm is more efficient by reducing the calculation steps, preserving the co-registration accuracy, and minimizing the need for elevation normalization in dense urban areas.
机译:光学图像和高程数据的集成对于3D辅助制图应用非常重要。超高分辨率(VHR)卫星图像为映射建筑物信息提供了理想的地理数据。由于建筑物本质上是高架物体,因此需要将这些图像与其高程数据进行配准,以获得可靠的建筑物检测结果。但是,对于在稠密城市地区获取的最低点VHR图像而言,精确的共配准非常困难。因此,本研究提出了一种基于视差的高程共配准(DECR)方法,以生成视线数字表面模型(LoS-DSM),以有效实现像素级精度的图像高程数据共配准。相对于传统的摄影测量方法,得出的高程的RMSE值小于2个像素。 DECR方法的适用性通过在具有挑战性的密集城市地区中基于高程的建筑物检测(EBD)得以证明。发现检测结果的质量大于90%。此外,将检测到的物体成功地地理参考到了它们正确的地面位置,从而可以与其他地图直接集成。与原始的LoS-DSM开发算法相比,DECR算法的效率更高,它减少了计算步骤,保留了共配准精度,并最大限度地减少了人口稠密城市地区的海拔标准化。

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