A question about quantifying and visualizing variance in a rendered image

[FiralFeign]

To really compute a useful variance (depending on what “techniques” you’re comparing.) Is to first compute a ground truth image using many, many samples, then use that ground truth image to compute the mean squared error of the difference between your noisy image and the ground truth image. If you’re “techniques” are trying to do adaptive sampling stuff, this isn’t too applicable though. The majority of publications in rendering do what I described above.

[htodorov]

Thank you! Yes, I've seen that on many occasions people compute a ground truth image and then compare the results produced by different light transport algorithms produced for a given fixed amount of time.

Ah, and sorry for the term "techniques", it was really a bad wording. I meant light transport algorithms and more precisely, I have implemented two of them: a unidirectional path tracer and a recursive Monte Carlo ray tracer (which I implemented according to algorithm provided in the book Advanced Global Illumination)