https://github.com/wenbihan/frist_ivp2017
https://github.com/wenbihan/frist_ivp2017
image-denoising mri-reconstruction rotation-invariant sparse-coding transform-learning unsupervised-learning
Last synced: 8 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/wenbihan/frist_ivp2017
- Owner: wenbihan
- Created: 2018-02-05T02:33:51.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-02-05T04:49:32.000Z (over 7 years ago)
- Last Synced: 2025-01-07T18:18:40.309Z (9 months ago)
- Topics: image-denoising, mri-reconstruction, rotation-invariant, sparse-coding, transform-learning, unsupervised-learning
- Language: Matlab
- Size: 4.29 MB
- Stars: 5
- Watchers: 2
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# FRIST learning and applications
=============
FRIST learning accompanies the following publications:
1. "FRIST — flipping and rotation invariant sparsifying transform learning and applications", International Inverse Problems (IVP), 2017. [IVP 2017](http://iopscience.iop.org/article/10.1088/1361-6420/aa6c6e/meta), [PDF available](http://web.engr.illinois.edu/~bwen3/asset/IVP_FRIST_2017.pdf)
2. "Learning Flipping and Rotational Invariant Sparsifying Transform", Proc. IEEE International Conference on Image Processing (ICIP), 2016. [ICIP 2016](http://ieeexplore.ieee.org/abstract/document/7533082/), [PDF available](http://web.engr.illinois.edu/~bwen3/asset/icip2016-frist.pdf), [Poster](http://transformlearning.csl.illinois.edu/assets/Bihan/ConferenceSlidesandPosters/BihanSaiICIP2016frist_poster.pdf)
Description:
-----
FRIST is a formulation and methodology for learning a Flipping and Rotation Invariant Sparsifying Transform, and simultaneously clusters the data via their directional orientation.
The FRIST package includes (1) a collection of the FRIST Matlab functions, and (2) example demo data used in the FRIST paper including image denoising, and MRI reconstruction.
You can download our other software packages at: [My Homepage](http://web.engr.illinois.edu/~bwen3/) and [Transform Learning Site](http://transformlearning.csl.illinois.edu/).
Paper
In case of use, please cite our publications:
1. B. Wen, S. Ravishankar, and Y. Bresler, “FRIST Flipping and Rotational Invariant Sparsifying Transform Learning and Applications,” Inverse Problems (IVP), vol. 33, no. 7, 2017.
```
@article{wen2017frist,
title={{FRIST} — flipping and rotation invariant sparsifying transform learning and applications},
author={Wen, Bihan and Ravishankar, Saiprasad and Bresler, Yoram},
journal={Inverse Problems},
volume={33},
number={7},
pages={074007},
year={2017},
publisher={IOP Publishing}
}
```
2. B. Wen, S. Ravishankar, and Y. Bresler. “Learning flipping and rotation invariant sparsifying transforms," IEEE International Conference on Image Processing (ICIP), pp. 3857-3861, 2016.
```
@inproceedings{wen2016learning,
title={Learning flipping and rotation invariant sparsifying transforms},
author={Wen, Bihan and Ravishankar, Saiprasad and Bresler, Yoram},
booktitle={Image Processing (ICIP), 2016 IEEE International Conference on},
pages={3857--3861},
year={2016},
organization={IEEE}
}
```
Use
---
All codes are subject to copyright and may only be used for non-commercial research. In case of use, please cite our publication.
Contact Bihan Wen (bihan.wen.uiuc@gmail.com) for any questions.
Acknowledgement
---
The development of this software was supported in part by the National Science Foundation (NSF) under grants CCF 06-35234 and CCF 10-18660.