Nobody testing DxO PureRAW seems to care about how much detail the neural network "invents"
Hi,
I agree with this sentence. But here it's exactly what the step is supposed to do. And it's also what does every demosaicing algorithm.
On Pureraw, the whole demosaicing operation is done by the nn, and they include sensor-specific noise in the training (and maybe some artifacts, like fringing, glare, etc).
The denoising from deepprime is very well placed in the raw pipeline, where it works with a maximum of efficiency, already starting to deal with the noise before any demosaicing operation.
Maybe you already know this link :
https://blog.dxo.com/denoising-technology/In practice, By experience, it's close to what you measured, 2EV increase in DR compared to a more regular algorithm like Adobe CR. The difference is also visible at all the iso stages, but high iso images is clearly where the algorithm outperform everything i saw on the market. One of the main drawbacks from a photographer's experience is that it can produce a kind of color quantization in challenging conditions or dark areas, which can be difficult to manage then in post production.
But clearly, it is worth the try, artifacts/drawbacks remain very well controlled
In practice, I also noticed the drastical gain that can produce the deepprime on old camera models (It made me change my mind on old images I never used considering noise).
in comparison, topaz tools (denoising, gigapixels, sharpen) are impressive too but are more prone to change the structure of the image and introduce some small artifacts. Ok, they deal with bitmap images, and it's another deal than raw datas.
I would recommend these tools at the end of the workflow, or at least when the final destination is known, in order to avoid the upsampling of these artifacts when upsampling a file.