Image Reconstruction of Static and Dynamic Scenes through Anisoplanatic Turbulence

This repository contains the code for the following paper:

Zhiyuan Mao, Nicholas Chimitt, and Stanley H. Chan, ‘‘Image reconstruction of static and dynamic scenes through anisoplanatic turbulence’’, IEEE Trans. Computational Imaging, vol. 6, pp. 1415-1428, Oct. 2020.

How to use:

Check the demo.m file
We've prepared a few sets of parameters for low, medium and high turbulence level (corresponding to D/r0 = 1.5, 3, and 4.5)

Packages included

Algorithm for image reconstruction through atmospheric turbulence, developed by Purdue i2Lab
Plug and Play ADMM, developed by Purdue i2Lab
Optical flow, developed by Ce Liu (Microsoft Research New England) https://people.csail.mit.edu/celiu/OpticalFlow/

The data used in the paper can be downloaded here:

https://drive.google.com/file/d/1VsQyrPexjAXegAXAx7A5CmKB0F4hw_O7/view?usp=sharing

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

@ARTICLE{mao_tci,
  author={Zhiyuan Mao and Nicholas Chimitt and Stanley H. Chan},
  journal={IEEE Transactions on Computational Imaging}, 
  title={Image Reconstruction of Static and Dynamic Scenes Through Anisoplanatic Turbulence}, 
  year={2020},
  volume={6},
  pages={1415-1428},
  doi={10.1109/TCI.2020.3029401}
  }

Please also check out our other work on Atmospheric Turbulence:

LICENSE

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

TurbRecon_TCI/README.md

Image Reconstruction of Static and Dynamic Scenes through Anisoplanatic Turbulence

LICENSE