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Comment by rhplus | Hacker News Reader

I just noticed that this is from a 2009 paper. Has this method made its way into any products by now?

Techniques like this have been used in some high-end sensor applications since (at least) the 1990s. It was an option for increasing discrimination resolution via DSP that could not practically be accomplished via higher resolution sensors due to things like space constraints given the technology of the time. It is probably less useful today due to ongoing miniaturization of imaging sensors.

> It is probably less useful today due to ongoing miniaturization of imaging sensors.

Not really. Dig into concepts called sparsity and compressed sensing, which are quite similar algorithms (not really the algorithms, but the underlying ideas).

I can't find the authors' original website, only this old wired article from 2010: http://www.wired.com/magazine/2010/02/ff_algorithm/2/

So especially with the ongoing miniaturization of imaging sensors, which will allow you to take even bigger and bigger pictures, there are issues these algorithms could solve, unless SD cards get really cheap really fast I guess.

I meant less useful for the purposes which such algorithms were originally designed for two decades ago. They original use cases were discrimination, not making prettier pictures. I am quite familiar with compressive sampling.

Thanks for the link. I'm now in the process of choosing the direction of my postgraduate studies, and these things quasifractal-related seem rather interesting.

If you have Matlab, you might try the tools here:

http://www.ece.lsu.edu/ipl/Software.html

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