Multiple views of Lutetia taken from OSIRIS NAC payload can be used to perform a metric reconstruction 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 (approximately) 1.5 million of points is derived using two views. The dense model has a resolution which is approximately 120 m/px and contains the surface topography up to 1 km scale.

Lutetia surface reconstruction and uncertainty analysis

DEBEI, STEFANO;ABOUDAN, ALESSIO;COLOMBATTI, GIACOMO;PERTILE, MARCO
2012

Abstract

Multiple views of Lutetia taken from OSIRIS NAC payload can be used to perform a metric reconstruction 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 (approximately) 1.5 million of points is derived using two views. The dense model has a resolution which is approximately 120 m/px and contains the surface topography up to 1 km scale.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2532942
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