Refined equivalent pinhole model for large-scale 3D reconstruction from spaceborne CCD imagery

Danyang Hong, Anzhu Yu, Song Ji, Xuanbei Lu, Wenyue Guo, Xuefeng Cao, Chunping Qiu
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Abstract

Automatic 3D reconstruction from spaceborne charge-coupled device (CCD) optical imagery is still a challenge as the rational functional model (RFM) based reconstruction pipeline failed to amount to the advances of pinhole based approaches in computer vision and photogrammetry. As a consequence, the accuracy and completeness of the reconstructed surface by RFM based pipeline improved slightly recent years. Though the perspective camera approximation model was explored to convert the RFM to pinhole model, it could hardly guarantee the reconstruction accuracy due to the re-projection error introduced when approximating the linear push broom camera to perspective camera. Hence, we present a refined equivalent pinhole model (REPM) for 3D reconstruction from spaceborne CCD imagery. We initially investigated the aspects that influence the re-projection error thru mathematical induction and discovered that the image size and height range of the captured area are the two key factors. To ensure the performance of the 3D reconstruction while minimizing the re-projection error, we explored the optimal image size to crop large-scale image with, while alleviated the height range effect on the image space by re-projecting the cropped images to be closed to the pseudo-image that is captured by the approximated perspective camera. The above-mentioned improvements are implemented in an image partition module and an image geometric correction module respectively, and are encompassed in the proposed REPM-based 3D reconstruction pipeline. We conducted extensive experiments on different images covering various areas from different linear-array CCD sensors to verify the proposed approach. The results indicate that our pipeline can achieve higher accuracy and completeness and exhibits great potential. The implementation of the pipeline is available at here.

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利用空间 CCD 图像进行大规模 3D 重建的改进等效针孔模型
从空间电荷耦合器件(CCD)光学图像进行自动三维重建仍然是一项挑战,因为基于合理函数模型(RFM)的重建管道未能赶上计算机视觉和摄影测量领域基于针孔方法的进步。因此,基于 RFM 的重建管道重建表面的精度和完整性近年来略有提高。虽然人们探索了将 RFM 转换为针孔模型的透视相机近似模型,但由于将线性推帚相机近似为透视相机时会引入重投影误差,因此很难保证重建精度。因此,我们提出了一种用于空间 CCD 图像三维重建的精制等效针孔模型(REPM)。我们通过数学归纳法初步研究了影响重投影误差的各个方面,发现图像尺寸和捕获区域的高度范围是两个关键因素。为了在确保三维重建性能的同时尽量减小重投影误差,我们探索了裁剪大尺度图像的最佳图像尺寸,同时通过对裁剪后的图像进行重投影,使其与近似透视相机拍摄的伪图像相接近,从而减轻了高度范围对图像空间的影响。上述改进分别在图像分割模块和图像几何校正模块中实现,并包含在所提出的基于 REPM 的三维重建流水线中。我们对来自不同线性阵列 CCD 传感器、覆盖不同区域的不同图像进行了大量实验,以验证所提出的方法。结果表明,我们的管道可以实现更高的精度和完整性,并展现出巨大的潜力。该管道的实现方法可在此处获取。
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来源期刊
International journal of applied earth observation and geoinformation : ITC journal
International journal of applied earth observation and geoinformation : ITC journal Global and Planetary Change, Management, Monitoring, Policy and Law, Earth-Surface Processes, Computers in Earth Sciences
CiteScore
12.00
自引率
0.00%
发文量
0
审稿时长
77 days
期刊介绍: The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
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