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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:

The code with simulator_old.py is tested with the following environment:

  • Python 3.6
  • Pytorch 1.4.0
  • Numpy 1.19.2
  • Scipy 1.6.0
  • Matplotlib 3.3.6

Update: we modify the code to work with pytorch 1.10 and beyond. Please use the latest simulator.py. Nothing else has changed. For pytorch 1.4, use simulator_old.py. The difference is due to the pytorch's update on the fft module.

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:

This software is made available for evaluation purposes only and has features which are patent pending.

LICENSE

CC BY-NC-SA 4.0

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

CC BY-NC-SA 4.0

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