114 - Automatic image quality assessment using BRISQUE

BRISQUE calculates the no-reference image quality score for an image using the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE).

BRISQUE score is computed using a support vector regression (SVR) model trained on an image database with corresponding differential mean opinion score (DMOS) values. The database contains images with known distortion such as compression artifacts, blurring, and noise, and it contains pristine versions of the distorted images. The image to be scored must have at least one of the distortions for which the model was trained.

This tutorial explains the use of BRISQUE in Python.

Mittal, A., A. K. Moorthy, and A. C. Bovik. "No-Reference Image Quality Assessment in the Spatial Domain.
" IEEE Transactions on Image Processing. Vol. 21, Number 12, December 2012, pp. 4695–4708.

https://live.ece.utexas.edu/publicati...

To install imquality:
https://pypi.org/project/image-quality/

The code from this video is available at: https://github.com/bnsreenu/python_fo...