MSU Brightness Independent PSNR (BI-PSNR)

Common idea

BI-PSNR metric is intended for measuring distortions in video taking into account brightness shifts.

Change Log

[!] — Known bug
[+] — New Feature
[*] — Other

Version 1.1
[*] Visualization bug fixed for non-stadard resolution video

Version 1.0
[+] First plugin release


BI-PSNR metric should be used when one of the sequences has any brightness transformation, which does not change within frame. Example of such transformation is uniform increasing of brightness of contrast for single frame of for all sequence. Such transformations prevent usage of standard metrics because of strong brightness difference between comparing frames. BI-PSNR algorithm calculates brightness transformation, which makes frames similar as possible and calculates standard PSNR and MSE metrics taking into account founded transformation.


There are two part of visualization:

Example of
Example of visualization
Visualization of the same frame using standard
Visualization of the same frame using standard PSNR


Plots of per-frame PSNR values after the found transformation are drawing after all calculations. Plots are entirely the same as standard per-frame PSNR

Plot's example
Standard PSNR plot for the same
Standard PSNR plot for the same sequence


Table C[i,j] is filling for each frame: C[i,j] = { number of points in the same position, which have brightness i at the first sequence frame and j at the second sequence frame }

Next, for each i (brightness value from the first frame) we find corresponding brightness from the second sequence. Following formula is used to estimate distanse from arbitrary values of i and j:

One can note that this formula is sum of quadratic differences between all pixels of the first sequence with value i and all corresponding pixels from second sequence on the assumption that brightness was shifted to i-j.

When transformation was found, we can find MSE for the frame taking into account this transformation:




10 May 2017
See Also
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Parallax determines the depth of S3D movies. The range of parallaxes should be both comfortable and entertaining for spectators.
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MSU Video Quality Measurement Tool (VQMT) is a program for objective video quality assessment.
MSU VQMT Subjective quality correlation
Comparison provided for the most popular metrics: PSNR, SSIM, 3-SSIM, MS-SSIM and new stSSIM
MSU Video Quality Measurement Tool: SDK
MSU Perceptual Video Quality: Subjective video quality methods information
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