Developer Reference

  • 2020
  • 10/21/2020
  • Public Content
Contents

Image Quality Index

Intel IPP functions described in this section compute the universal image quality index [Wang02] that may be used as image and video quality distortion measure. It is mathematically defined by modeling the image distortion relative to the reference image as a combination of three factors: loss of correlation, luminance distortion, and contrast distortion.
If two images
f
and
g
are considered as a matrices with
M
column and
N
rows containing pixel values
f
[
i,j
],
g
[
i,j
], respectively (0 ≥
i
>
M
, 0 ≥
j
>
N
), the universal image quality index
Q
may be calculated as a product of three components:
where
The first component is the correlation coefficient, which measures the degree of linear correlation between images
f
and
g
. It varies in the range [-1, 1]. The best value 1 is obtained when
f
and
g
are linearly related, which means that
g
[
i,j
]
=
af
[
i,j
]
+b
for all possible values of
i
and
j
. The second component, with a value range of [0, 1], measures how close the mean luminance is between images. Since
σ
f
and
σ
g
can be considered as estimates of the contrast of
f
and
g
, the third component measures how similar the contrasts of the images are. The value range for this component is also [0, 1].
The range of values for the index
Q
is [-1, 1]. The best value 1 is achieved if and only if the images are identical.

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.