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# TurbulenceSim_P2S
# Accelerating Atmospheric Turbulence Simulation via Learned Phase-to-Space Transform

This repository contains the code for the following paper:

Zhiyuan Mao, Nicholas Chimitt, and Stanley H. Chan, ‘‘Accelerating Atmospheric Turbulence Simulation via Learned Phase-to-Space Transform’’, accepted to ICCV 2021

Arxiv:
https://arxiv.org/abs/2107.11627

How to use:
- Check the demo.py file
- The generation of correlation matrix for point spread functions is slow. We have prepared a few correlation matrix with different correlation strength for you to download at _____________________________

If you find our work helpful in your research, please consider cite our paper

```
@InProceedings{Mao_2021_ICCV,
author = {Zhiyuan Mao and Nicholas Chimitt and Stanley H. Chan},
title = {Accelerating Atmospheric Turbulence Simulation via Learned Phase-to-Space Transform},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2021}
}
```

Please also check out our other work on Atmospheric Turbulence:
- Project page

https://engineering.purdue.edu/ChanGroup/project_turbulence.html

- Reconstruction of static and dynamic scene through atmospheric turbulence:

_________________________________________________________________

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