Optimal Self-Calibration Strategies in the Combined Bundle Adjustment of Aerial-Terrestrial Integrated Images
Optimal Self-Calibration Strategies in the Combined Bundle Adjustment of Aerial-Terrestrial Integrated Images
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DOI：
10.3390/rs14091969
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发表时间：
2022-04
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通讯作者：
Linfu Xie;Han Hu;Qing Zhu;Xiaoming Li;Xiang Ye;R. Guo;Yeting Zhang;Xiaoqiong Qin;Weixi Wang-Weixi
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作者：
Linfu Xie;Han Hu;Qing Zhu;Xiaoming Li;Xiang Ye;R. Guo;Yeting Zhang;Xiaoqiong Qin;Weixi Wang-Weixi
精确的组合光束法平差（BA）是从互补平台获取的航空和陆地图像集成的基本步骤。在传统的摄影测量流水线中，自校准光束法平差（SCBA）通过同时修正包括透镜畸变参数在内的内方位参数（IOP）和外方位参数（EOP）来提高BA精度。航空和地面图像分别通过SCBA处理，需要使用BA融合。因此，必须正确处理空-地BA中的IOP。一方面，对于物理上相同的图像，一次飞行中的IOP应该是相同的。另一方面，跨平台组合BA中的IOP调整可以在数学上提高3D空间中的空中-地面图像共配准程度。本文研究了航地影像块联合BA中自标定策略对配准精度的影响。为了回答这个问题，从七个研究区域捕获的航空和陆地图像进行了测试，在四个空中-陆地BA场景：空中和陆地图像的IOP是固定的;仅空中图像的IOP是固定的;仅陆地图像的IOP是固定的;两个图像的IOP都进行了调整。根据两个平台上可见的独立检查点评价BA的跨平台共配准准确度。实验结果表明，在BA期间，航空图像的恢复IOP应该是固定的。然而，当地面图像的连接点广泛地分布在图像空间中并且空中图像网络足够稳定时，在BA期间细化地面相机的IOP可以提高配准精度。否则，修复IOPS是最好的解决方案。
Accurate combined bundle adjustment (BA) is a fundamental step for the integration of aerial and terrestrial images captured from complementary platforms. In traditional photogrammetry pipelines, self-calibrated bundle adjustment (SCBA) improves the BA accuracy by simultaneously refining the interior orientation parameters (IOPs), including lens distortion parameters, and the exterior orientation parameters (EOPs). Aerial and terrestrial images separately processed through SCBA need to be fused using BA. Thus, the IOPs in the aerial–terrestrial BA must be properly treated. On one hand, the IOPs in one flight should be identical for the same images in physics. On the other hand, the IOP adjustment in the cross-platform-combined BA may mathematically improve the aerial–terrestrial image co-registration degree in 3D space. In this paper, the impacts of self-calibration strategies in combined BA of aerial and terrestrial image blocks on the co-registration accuracy were investigated. To answer this question, aerial and terrestrial images captured from seven study areas were tested under four aerial–terrestrial BA scenarios: the IOPs for both aerial and terrestrial images were fixed; the IOPs for only aerial images were fixed; the IOPs for only terrestrial images were fixed; the IOPs for both images were adjusted. The cross-platform co-registration accuracy for the BA was evaluated according to independent checkpoints that were visible on the two platforms. The experimental results revealed that the recovered IOPs of aerial images should be fixed during the BA. However, when the tie points of the terrestrial images are comprehensively distributed in the image space and the aerial image networks are sufficiently stable, refining the IOPs of the terrestrial cameras during the BA may improve the co-registration accuracy. Otherwise, fixing the IOPs is the best solution.