This filter has been created
following the ideas of Zhou
Wang.
It has been coded with the great help of Mfa, who worked on the core functions.
For a given reference video and a given compressed video, it is meant to compute
a quality metric, based on perceived visual distortion. Unlike the well-known
PSNR measure, it's not purely mathematical, and should correlate much better
with human vision.
Some examples can be found here.
A higher MSE (and so lower PSNR) should mean that the compressed clip is a worse
image but MSE and PSNR are flawed in this respect as numerous tests have shown.
However with SSIM, according to tests carried out on the VQEG dataset, a higher
Q (SSIM value) has a much better relation to the visual quality of the
compressed clip. Despite this, bear in mind the SSIM metric still isn't perfect.
This filter is designed to compute an SSIM value by two methods, the original
one, and a "enhanced" one that weight these results by lumimasking. On
the todo list is to include the motion weighting.
This filter has five parameters:
code:
ssim(clip1,clip2,"results.csv","averageSSIM.txt",lumimask=true)