A Generic Bundle Adjustment Methodology for Indirect RPC Model Refinement of Satellite Imagery
Roger Marí, Carlo de Franchis, Enric Meinhardt-Llopis, Jérémy Anger, Gabriele Facciolo
published
2021-11-13
reference
Roger Marí, Carlo de Franchis, Enric Meinhardt-Llopis, Jérémy Anger, and Gabriele Facciolo, A Generic Bundle Adjustment Methodology for Indirect RPC Model Refinement of Satellite Imagery, Image Processing On Line, 11 (2021), pp. 344–373. https://doi.org/10.5201/ipol.2021.352

Communicated by Pascal Monasse
Demo edited by Roger Marí

Abstract

This article describes a generic bundle adjustment methodology for multi-view stereo pipelines for 3D reconstruction from high-resolution optical satellite imagery. The Rational Polynomial Camera (RPC) model of each input view is refined by composing it with a rotation that compensates errors related to the attitude angles encoding the satellite orientation. A set of tie points, derived from feature tracks detected across the input images, is used to find the optimal corrective rotations by minimization of the reprojection error. We evaluate the performance of our method using time series of SkySat acquisitions over two different areas of interest. As an internal evaluation metric we compute the standard deviation between corresponding height estimations derived from different stereo pairs, before and after the bundle adjustment correction. Lastly, the results are also compared to an alternative solution for multi-view stereo pipelines that eludes any explicit correction of the camera models by directly registering independent dense surface models.

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