Blind Image Quality Assessment of Authentically Distorted Images
Code for the paper Blind Image Quality Assessment of Authentically Distorted Images (JOSA A).
Proposed architecture
Dependencies
- Python 3.8
- PyTorch 1.5.1
- Torchvision
- Cuda 11.4
Reference
If you have any question, please do not hesitate to contact luigi.celona@unimib.it
If you find this code useful to your research, please consider citing:
- Luigi Celona, and Raimondo Schettini. Blind Image Quality Assessment of Authentically Distorted Images. In JOSA A, volume 39, number 4, pp. -, 2022.
@article{celona2022blind,
author = {Celona, Luigi and Schettini, Raimondo},
title = {Blind Quality Assessment of Authentically Distorted Images},
journal = {Journal of the Optical Society of America A},
volume = {39},
year = {2022},
number = {4},
pages = {B1--B10},
doi = {10.1364/JOSAA.448144}
}