Tomography of Turbulence Strength Based on Scintillation Imaging
Abstract
Developed areas have plenty of artificial light sources. As the stars, they appear to twinkle, i.e., scintillate. This effect is caused by random turbulence. We leverage this phenomenon in order to reconstruct the spatial distribution the turbulence strength (TS). Sensing is passive, using a multi-view camera setup in a city scale. The cameras sense the scintillation of light sources in the scene. The scintillation signal has a linear model of a line integral over the field of TS. Thus, the TS is recovered by linear tomography analysis. Scintillation offers measurements and TS recovery, which are more informative than tomography based on angle-of-arrival (projection distortion) statistics. We present the background and theory of the method. Then, we describe a large field experiment to demonstrate this idea, using distributed imagers. As far as we know, this work is the first to propose reconstruction of a TS horizontal field, using passive optical scintillation measurements.
Cite
Text
Shaul and Schechner. "Tomography of Turbulence Strength Based on Scintillation Imaging." Proceedings of the European Conference on Computer Vision (ECCV), 2022. doi:10.1007/978-3-031-20071-7_28Markdown
[Shaul and Schechner. "Tomography of Turbulence Strength Based on Scintillation Imaging." Proceedings of the European Conference on Computer Vision (ECCV), 2022.](https://mlanthology.org/eccv/2022/shaul2022eccv-tomography/) doi:10.1007/978-3-031-20071-7_28BibTeX
@inproceedings{shaul2022eccv-tomography,
title = {{Tomography of Turbulence Strength Based on Scintillation Imaging}},
author = {Shaul, Nir and Schechner, Yoav Y.},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2022},
doi = {10.1007/978-3-031-20071-7_28},
url = {https://mlanthology.org/eccv/2022/shaul2022eccv-tomography/}
}