CG image quality evaluation memo in Python

background

I want to do it easily with Jupyter-lab + numpy / scipy.

It is not for people who do ordinary (?) Image processing in the world.

Common method

SSIM

In skimage

https://scikit-image.org/docs/dev/auto_examples/transform/plot_ssim.html

SNR

It seems to be in scipy, but the expression itself is easy, so it seems better to write it in numpy

https://github.com/scipy/scipy/issues/9097

https://www.codespeedy.com/calculate-signal-to-noise-ratio-in-python/

Method for CG

FLIP

ꟻLIP: A Difference Evaluator for Alternating Images https://research.nvidia.com/publication/2020-07_FLIP

Freshly made with HPG2020.

It seems that it can be used for calculating the error between CG and live action, so it is offered to users like us.

There are implementations in various languages, including implementations in numpy / scipy.

Other

Detecting Bias in Monte Carlo Renderers using Welch’s t-test http://jcgt.org/published/0009/02/01/

For Monte Carlo rendering. There may be python code here as well.

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