AMD's FidelityFX Super Resolution Launched and Tested; Nvidia's DLSS Coming to Linux

takyon writes:

Testing AMD's FidelityFX Super Resolution (FSR): Image Analysis and Preliminary Performance

The most prominent form of [upscaling algorithm] today is Nvidia's [Deep Learning Super Sampling (DLSS)], the company's proprietary AI-based temporal upscaling solution that runs on GeForce RTX GPUs. Temporal upscaling means data is accumulated from multiple frames and combined into the final image, with the AI component running on Nvidia's Tensor cores to assist with this reconstruction. DLSS has gone through more than one iteration, and right now at version 2.0, it's a major improvement over the initial release and it's also gathered decent game support after much work from Nvidia.

[AMD's FidelityFX Super Resolution (FSR)] takes a different approach. Instead of using temporal upscaling, FSR relies exclusively on spatial upscaling. AMD tells us that AI is not used at any stage of the FSR process (so FSR is not the technology described in that patent that's been floating around). This greatly simplifies the algorithm - spatial upscaling does not rely on data from multiple frames, or motion vectors, which makes it easier to integrate into games as there are less data inputs. However, with less data to work with, spatial upscaling algorithms need to be really good at figuring out how to reconstruct the image, and traditionally this is where they've fallen short.

AMD hasn't gone into great detail on how their algorithm works, but they tell us this is not a simple rehash of bilinear upscaling, which is the 'standard' method for spatial upscaling. AMD calls their technique an "advanced edge reconstruction algorithm," which is combined with a sharpening pass to create the final image. There is only one input to the algorithm, which is the lower resolution frame.

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