State of the art in upsizing algorithms?

Started Jun 9, 2014 | Discussions thread
hjulenissen Senior Member • Posts: 2,269
Re: State of the art in upsizing algorithms?

Doing the processing "joint" as opposed to stage-wise might be expected to always be at least as good or better. One might also expect it to always be harder. In the end, each output pixel will probably mainly depend on a (small-ish) set of corresponding input pixels, plus some global/regional processing. If you can define this (nonlinear, signal-adaptive) function, then you can apply it in Octave or whatever.

The baseline for image scaling is working in some desirable domain (gamma vs linear, colour space, ...) and choosing the appropriate linear filter (some time vs frequency trade-off, for instance lanczos2/3). For some applications you might want to do post sharpening tightly integrated with the scaling operation. The ImageMagick link that you found is an excellent resource.

The "better than linear filtering" commercial applications that are available seems to often rely on some kind of edge-adaptive algorithm, meaning that sharp edges (e.g. text) can be blown up sharp and smooth.

I think that there are some applications of "non-local" methods for denoising/upscaling that might benefit certain kinds of images (i.e. exploiting image self-similarity).

If you put 100 monkeys in front of photoshop, they will (eventually) produce genuine works of art. Which is to say that if an image is really important to you, you can spend any amount of time in front of Photoshop (using both manual and automatic tools) to improve the image beyond what automatic tools are able to themselves as long as the quality metric is your own eyes.

For my own humble needs (18MP APS-C, A2 printer), I have found that the sensel grid is seldom a significant limitation (but lens quality/focus can be).

-h

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