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}
}