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Topaz ai gigapixel raw files examples
Topaz ai gigapixel raw files examples













topaz ai gigapixel raw files examples

Although TLG and all other such implementations supply interpolated “synthetic” pixels into the “expanded” image, by direct experiment with difficult keeper images I have, DeepPRIME and TLG both do a “better job” than the nearest Adobe commercially available equivalents. (The two Topaz applications in the noise and sharpen steps are independent, and do not cycle between the two.) Is this correct – thus in principle making the DxO integrated DeepPRIME design/implementation in some sense “better”?Īs an aside (my copyright images available), I have been experimenting with TLG after DeepPRIME, working on TIFF, JPEG, and DNG output images, with generally excellent results (more “keepers”). My understanding, also using some form of AI technology (neither Topaz Labs nor DxO have any technical engineering papers on which AI neural net, how may layers, etc., actually have been implemented in the software model and source program), is that DeepPRIME does the first two steps (denoise and sharpen) as a single “integrated” step (with multiple “passes” within the internals of the neural network, etc.) to get the best compromise between noise reduction and sharpness increase, not as two “independent” steps as (apparently) done by Topaz. In our (Topaz) AI products, the framework should be DeNoise AI → Sharpen AI → Gigapixel AI. Using Topaz Labs workflow, Topaz Labs recommends: I have been using Topaz Labs Gigapixel AI (TLG) (at least until DxO offers something “similar”).















Topaz ai gigapixel raw files examples