利用全局仿射模型进行卫星图像快速三维重建
Fast 3D Reconstruction of Satellite Images via global affine model
- 2022年 页码：1-14
网络出版日期： 2022-07-13
DOI： 10.11834/jrs.20222039
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摘要
基于多视角卫星遥感图像的三维场景重建是遥感领域中一项极具挑战性的任务。针对现有方法重建速度慢的问题，本文提出了一种利用全局式仿射模型进行卫星图像快速重建方法。该方法首先将多视角卫星图像裁剪成一组局部图像块并计算相应局部场景的三维仿射点云，然后引入一种基于局部点云的全局式仿射运动矩阵估计算法计算出每个视角对应的相机仿射运动矩阵，在此基础上利用少量地面控制点恢复出场景的三维欧氏结构。在两个公共数据集上的实验结果表明，本文方法的重建速度、精度和完整性在大多数情况下均优于三种主流文献方法。
Abstract
Objective 3D scene reconstruction based on multi-view satellite remote sensing images is a challenging task in the field of remote sensing. Most of the existing methods either have to perform bundle adjustment repeatedly or need to calculate a lot of parameters in the rational polynomial camera model
resulting in a relatively long reconstruction time. To solve the above-mentioned problems
this paper considers that the local small-sized patches in large-sized satellites could be approximately modeled by the affine imaging model
and proposes a fast 3D reconstruction method of satellite images based on global affine model estimation.Method First
the input multi-view satellite images are cropped into a set of small-sized patches with overlapping regions. For each pair of patches that have a sufficient number of point correspondences from two views
the corresponding 3D affine point cloud is calculated. Second
based on the obtained local point clouds
a global affine camera motion estimation algorithm is presented for calculating the affine motion matrices of the cameras corresponding to all the patches in a unified coordinate system. Finally
the obtained affine camera motion matrices and a small number of ground control points are utilized to recover the Euclidean scene structure.
Result
2
3D reconstruction is carried out for the same group of remote sensing images and all remote sensing images to verify the effectiveness of the method The proposed solution is compared with three state-of-the-art methods (i.e.
COLMAP
S2P
and JHUAPL). The experimental results on two public datasets (i.e.
MVS3DM and DFC2019) show that the proposed method outperforms the three comparison algorithms in most cases with respect to speed
accuracy
and completeness. In order to further verify the reconstruction accuracy of the method
this paper selects 15 complex scene areas from two public datasets
including complex scenes with built-up areas
shadow areas
and complex object areas. For 15 complex scenarios
the proposed method outperforms the three methods with respect to accuracy and completeness in most cases.Conclusion This paper proposes a fast reconstruction method of satellite images based on global affine model estimation algorithm. The method assumes that the local image tile in large-scale satellite remote sensing images conforms to the affine imaging model
and introduces a global affine motion matrix estimation algorithm based on local point clouds. As a result
the proposed solution can calculate the global affine motion matrix of each local image tile through only one bundle adjustment
significantly reducing the reconstruction running time. The experimental results show that the proposed method can quickly solve the global affine matrix corresponding to each image tile
and realize fast 3D reconstruction of remote sensing images.
关键词
三维重建卫星遥感图像仿射成像模型欧氏结构恢复全局仿射矩阵
Keywords
3D reconstructionsatellite imagesaffine imaging modelEuclidean structure updateglobal affine matrix
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北京师范大学 地理科学学部 遥感科学与工程研究院 遥感科学国家重点实验室
北京林业大学 省部共建森林培育与保护教育部重点实验室
信息工程大学 地理空间信息学院
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