DeepVibes: Correcting Microvibrations in Satellite Imaging With Pushbroom Cameras

In this article, we propose new algorithms for estimating microvibrations and correcting their effects in satellite imaging with linear pushbroom camera. We first design an accurate model of the acquisition process with a linear pushbroom camera, which incorporates the satellite attitude as parameters. Then, we propose a two-stage reconstruction method based on an identification neural network to identify the attitude, followed by a deep unrolled network to correct the microvibrations. We then evaluate the proposed framework on synthetic and real data, showing promising results for this challenging problem. Our results highlight the critical role of the focal plane’s geometry, to improve the microvibrations identifiability and, therefore, the reconstruction quality.