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arXiv · 2012.03223

Spatiotemporal tomography based on scattered multiangular signals and its application for resolving evolving clouds using moving platforms

Roi Ronen·Yoav Y. Schechner·Eshkol Eytan
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Abstract

We derive computed tomography (CT) of a time-varying volumetric translucent object, using a small number of moving cameras. We particularly focus on passive scattering tomography, which is a non-linear problem. We demonstrate the approach on dynamic clouds, as clouds have a major effect on Earth's climate. State of the art scattering CT assumes a static object. Existing 4D CT methods rely on a linear image formation model and often on significant priors. In this paper, the angular and temporal sampling rates needed for a proper recovery are discussed. If these rates are used, the paper leads to a representation of the time-varying object, which simplifies 4D CT tomography. The task is achieved using gradient-based optimization. We demonstrate this in physics-based simulations and in an experiment that had yielded real-world data.

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Roi Ronen, Yoav Y. Schechner, Eshkol Eytan. 2020-12-06. Spatiotemporal tomography based on scattered multiangular signals and its application for resolving evolving clouds using moving platforms. https://arxiv.org/abs/2012.03223

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