State of the art in upsizing algorithms?

Started Jun 9, 2014 | Discussions thread
The_Suede Contributing Member • Posts: 652
Projection of convex sets?

There are some papers on this, and also some examples of a time-optimized version.

It's an iterative solution, where the information you mentioned in the previous post is successively merged into each other while minimizing a standard error function.

It's hard to make this kind of algorithm "sharp" since you need good reject(ance?) of noise to avoid ringing in the solution. What you basically get is a very high quality result (good image shape correlation, high SPSNRR) but at a slightly lower HF detail contrast.

It normally responds well to sharpening and further scaling / supersampling though.

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