I have conducted more tests on the Op’s approach, to better understand what exactly happens to sampling.
The short version is simple: the bigger the speed gains, the higher the noise level in the image.
The tonal compression that happens using Reinhard Burn isn’t confined to values higher than 1.0 (so, “invisible” at the rendered exposure), and the spillage of lower sampling will impact also transitional areas (f.e. the falloff of a light cone).
That the noise may or may not be visible is not relevant: one has to assume that one sets a noise threshold fit for their intended use (f.e., the image will need exposing up, or the client’s display devices add unwanted contrast, etc.), and the fact that the uniformity and amount of noise level is impacted should provide for some concern.
This said, i tested with extreme values, and obtained the most extreme of results: the speed up is more than significant for the tested scene (about 25%), but the difference in noise level is also very visible (i have kept the N.T. to a visible level on purpose, of course.).
The contact sheet is too big to attach here, so i linked it on GDrive.
The top row is the default render settings (Max AA subdivs at 200, N.T. of 0.05), middle row is with burn at 0.01 and no CM applied to the render, while the bottom row is the same, but with the CM burnt into the render, so we know what the sampler has to work with.
In the first column, it’s important to check the “Max” values, as they determine the final image’s range.
Notice how the third row is around 1.0f as maximum, whereas the original image carried a 1400f max in places.
This is what drives lower sampling around the image.
The second column contains the noise analisys (central pixel against average of 3x3 kernel around it). To a brighter pixel will correspond a higher noise.
Notice how the second row is brighter than the first, sure sign noise in the ouput is higher there.
Also -for confirmation- notice how the very low range third row is low also in noise.
The sampler works towards this image matching the set noise threshold, and then (conditionally) multiplies this render back up to the results we see in row 2, thereby also multiplying noise amount.
In the tonal-compressed render, noise is on average some 25% higher (it’s not a coincidence that the render took 25% less time.).
Lastly, i added the sampleRate REs, but because the max AA was very high, it’s hard to tell what goes on in them.
So the fourth column uses another noise level analisys to then normalise their values to show the different sampling profiles.
Notice how the second and third row are essentially a match, with ample areas looking “patchy”, where the same areas in the first row are nicely filled in. (f.e. the central columns, the top-left deck, the top central woodden panels, and so on.).
Noise there will be higher, and there is a second, important point as side effect: denoising won’t work as well.
This is because the tonal-compressed render decouples the noiseLevel Re from the actual noise in the image as, unlike for the third row, we decouple what the sampler and the final render need to achieve by not applying colormapping to the image.
The noiseLevel Re will then be wrong precisely in the places where noise will be higher, suggesting it’s lower than it is, and as a result the denoising there won’t be as effective.
Of course, there are sliding scales to this, a higher burn will have less issues, but that’s because sampling will be more uniform, and rendertimes will be higher.
TL;DR: The OP’s mentioned trick comes at a cost in both noise level (becoming unpredictable for level and distribution), and denoising quality.
Quicker renders will have more noise, non-uniformly distributed, and not as well cleaned up by denoising.
The suggestion is to not use it at all, as the UI hints by leaving the options hidden in the “advanced” section.
As a reference to my previous mention of vrayBitmap: the scene rendered in less than 18 minutes, after conversion, compared to 21 and change (about 15%, give or take. The scene has about 600 textures.).
This, while matching noise levels and providing for slightly sharper detail in places (not all textures are very high resolution in this scene.), but otherwise leaving the image essentially identical by the pixel.