nnedi3 vs NeuronDoubler

[luquinhas0021]

I guess Spline 100 (5 taps) is better than nnedi3_rpow2, because is more sharper and faster than nnedi3.

[Groucho2004]

Originally Posted by luquinhas0021

I guess Spline 100 (5 taps) is better than nnedi3_rpow2, because is more sharper and faster than nnedi3.

You can't have your cake and eat it too:
Sharper algorithms -> more artefacts

Ultimately it's your decision what you can live with.

[luquinhas0021]

It's not like this! Algorithms that use Edge detection doesn't have artifacts, sometimes, and are sharpers.

[colours]

Originally Posted by luquinhas0021

It's not like this! Algorithms that use Edge detection doesn't have artifacts, sometimes, and are sharpers.

That's only true on the assumption that the edge detection is perfect.

[luquinhas0021]

Colours, explain me what oy wannted say when you said perfect Edge Detection. Perfect in what sense: all edges detection or none artifact detection?

[colours]

Perfect in the sense that it detects all the edges and only the edges.

This is obviously not a well-posed problem because (in the context of photography) the projection from three dimensions to two is lossy, not to mention that things sometimes don't even have hard, defined edges. Also, Moiré patterns tend to mess with edge detectors.

It's simply not possible for an upscaling algorithm to be free of artifacts in every case. (Unless the input is bandlimited and sampling theorem etc.)

Not that this is all too relevant to the thread; if I'm not mistaken (though I very well might be), using a neural network approach to upscaling is more like solving a maximum likelihood problem than doing explicitly edge-directed interpolation. It's probably not entirely accurate to call nnedi3 an "EDI" type of algorithm, for example. The edge-directedness is an emergent property, not something inherent to how it works.