Universal Quality Image Index
Full-Reference Quality Metrics
Description
The Universal Quality Image Index (UQI)s created by modeling an image distortion as a combination of loss of correlation, distortion of luminance, and contrast.
Interpretation
The UQI has a range from 0 to 1. An image with a UQI of 1 has a high quality. An image with a lot of distortion will have a low UQI.
Limits
UQI is simple to calculate and align well with the human perception of quality.
Only images showing the same scene should be compared.
Example
An image from a traffic surveillance camera in Germany is used to show the UQI results.
Reference Image
UQI of 0.593
UQI of 0.837
Tools and Libraries
Python
In Python the package sewar contains multiple image quality metrics. One of them is the UQI.
Install package:
pip install sewar
Calculate UQI:
from sewar.full_ref import uqi
import cv2
img_ref = cv2.imread('Reference_Image.png')
img_dark = cv2.imread('Image_Dark.png')
img_sun= cv2.imread('Image_Sunshine.png')
score_dark = uqi(img_ref,img_dark)
print("Score of dark image", score_dark)
score_sun = uqi(img_ref,img_sun)
print("Score of dark image", score_sun)