http://cg.ivd.kit.edu/publications/p201 ... n_2013.pdfOur proposed method combines the simulated annealing optimization method with MCMC integration. Intuitively, the “sharp peaks” of the integrand areregularized (smoothed out) in the beginningof the integration such that the Markov chaincan easily find them. In order to achieve consistency,the regularization is reduced throughout the integration.

## Path Space Regularization (aka the solution to SDS paths)

### Re: Path Space Regularization (aka the solution to SDS paths)

I think the paper says about the same what I wrote, just a little vaguely worded:

### Re: Path Space Regularization (aka the solution to SDS paths)

They talk of "throughout the integration" or "mutation number" (without large or small qualifier). It is very generic and unclear.provisory wrote: ↑Thu Sep 19, 2019 4:48 pmI think the paper says about the same what I wrote, just a little vaguely worded:http://cg.ivd.kit.edu/publications/p201 ... n_2013.pdfOur proposed method combines the simulated annealing optimization method with MCMC integration. Intuitively, the “sharp peaks” of the integrand areregularized (smoothed out) in the beginningof the integration such that the Markov chaincan easily find them. In order to achieve consistency,the regularization is reduced throughout the integration.

Anyway, I have gone back to my initial idea of using a mollifies count for each pixel: this has several benefices. The "angles" will remain "large" until when a path affecting the pixel is not found, it will also shrink according the single pixel samples count, not the overall image samples count.

It seems the best compromise at the moment:

### Re: Path Space Regularization (aka the solution to SDS paths)

Look like you render the pool always without sky diffuse light. only sun. i think HDRI or sun + Sky can make the pool more clear.

### Re: Path Space Regularization (aka the solution to SDS paths)

Did you examine their sample implementation?

http://cg.ivd.kit.edu/publications/p201 ... 3_supp.pdf

I have too little knowledge for this, unfortunately.

http://cg.ivd.kit.edu/publications/p201 ... 3_supp.pdf

I have too little knowledge for this, unfortunately.

### Re: Path Space Regularization (aka the solution to SDS paths)

starting to look good. (except the overall darkness underwater)

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### Re: Path Space Regularization (aka the solution to SDS paths)

There's also "Hierarchical Russian Roulette for Vertex Connections", though it is implemented in BiDir and may not work with Hybrid.

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### Re: Path Space Regularization (aka the solution to SDS paths)

This statement is pretty clear to me as it comes from the field of many-body physics where the simulated annealing is used extensively. The general idea is to start from a "hot" system and let the MC equilibrate such that it samples the correct distribution at the given "temperature" (mollification). Then we gradually reduce the temperature slow enough to let MC adjusts itself to the new distribution at each moment. This is why there is a particular speed of temperature drop (like gamma^n for mollification) which should not be exceeded and which follows from the Metropolis rate of convergence.

In the end it should not matter what is n - a small mutations number or large mutations number, since they are proportional to each other.

BTW, I tried the smallpt code from the Supplemental Material and it is broken . After fixing it seems to work but produces a bit more fireflies as compared to the figure in the SM. It does not darken as far as I can see.

Last edited by Vutshi on Fri Sep 20, 2019 1:45 pm, edited 1 time in total.

### Re: Path Space Regularization (aka the solution to SDS paths)

what about sun+sky or HDRi