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Lutetia surface reconstruction and uncertainty analysis

机译：黄体表面重建和不确定性分析

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Multiple views of Lutetia taken from OSIRIS NAC payload can be used to perform a metric recon struction of its shape. In this work a general photogrammetric processing pipeline is described and a detailed uncertainty analysis is performed according with the standard metrological procedures. The uncertainty associated with the following quantities are highlighted and evaluated: intrinsic and extrinsic parameters of the multi-view system; the selected image feature detector and descriptor, which contribute to uncertainties associated with the used feature positions in each image plane; the lighting of the scene, which causes a not negligible uncertainty contribution to 2D positions in the image plane. The Bundle Adjustment, at the core of the reconstruction process, allows the assignment of the covariance of each input parameter and the estimation of derived 3D points covariance. The output covariance matrices represent the spatial uncertainty (magnitude and direction) of each reconstructed point and can be used to derive bounds on the uncertainty of other products as dense surface models and other physical parameters. Presented model of Lutetia is derived using 14 NAC images at the closest approach, 8042 features are tracked between consecutive frames and a final point cloud of 2590 points is produced. From the adjusted camera parameters a dense model with (approximatively) 1.5 million of points is derived using two views. The dense model has a resolution which is approximatively 120 m/px and contains the surface topography up to 1 km scale.
机译：从OSIRIS NAC有效载荷获取的Lutetia的多个视图可用于执行其形状的度量重建。在这项工作中，描述了一般的摄影测量处理管道，并根据标准计量程序进行了详细的不确定性分析。突出并评估了与以下数量有关的不确定性：多视图系统的内在和外在参数；所选择的图像特征检测器和描述符，其导致与每个图像平面中所使用的特征位置相关的不确定性；场景照明，这对图像平面中的2D位置造成了不可忽略的不确定性贡献。捆绑调整是重建过程的核心，它允许分配每个输入参数的协方差并估算得出的3D点协方差。输出协方差矩阵表示每个重构点的空间不确定性（大小和方向），可用于导出其他产品的不确定性的界限，例如密集曲面模型和其他物理参数。在最近的方法中使用14个NAC图像导出了Lutetia的模型，在连续的帧之间跟踪了8042个特征，并生成了2590个点的最终点云。从调整后的摄像机参数中，使用两个视图可以得出具有（大约）150万个点的密集模型。稠密模型的分辨率约为120 m / px，包含高达1 km的表面地形。

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