Monotonicity Prior for Cloud Tomography

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12363)


We introduce a differentiable monotonicity prior, useful to express signals of monotonic tendency. An important natural signal of this tendency is the optical extinction coefficient, as a function of altitude in a cloud. Cloud droplets become larger as vapor condenses on them in an updraft. Reconstruction of the volumetric structure of clouds is important for climate research. Data for such reconstruction is multi-view images of each cloud taken simultaneously. This acquisition mode is expected by upcoming future spaceborne imagers. We achieve three-dimensional volumetric reconstruction through stochastic scattering tomography, which is based on optimization of a cost function. Part of the cost is the monotonicity prior, which helps to improve the reconstruction quality. The stochastic tomography is based on Monte-Carlo (MC) radiative transfer. It is formulated and implemented in a coarse-to-fine form, making it scalable to large fields.


Scattering Regularization Physics-based vision 



We thank Ilan Koren, Eshkol Eytan Liebeskind, and Tom Dror-Schwartz for useful discussions. We thank Johanan Erez, Ina Talmon and Daniel Yagodin for technical support. Yoav Schechner is the Mark and Diane Seiden Chair in Science at the Technion. He is a Landau Fellow - supported by the Taub Foundation. His work was conducted in the Ollendorff Minerva Center. Minvera is funded through the BMBF. This research is funded by the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation program (grant agreement No 810370: CloudCT). Aviad Levis is a Zuckerman Postdoctoral Fellow.

Supplementary material

504473_1_En_17_MOESM1_ESM.pdf (656 kb)
Supplementary material 1 (pdf 655 KB)


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Viterbi Faculty of Electrical EngineeringTechnion - Israel Institute of TechnologyHaifaIsrael
  2. 2.Computing and Mathematical Sciences DepartmentCalifornia Institute of TechnologyPasadenaUSA

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