Computational photography overview

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Published on: November 8, 2020

An interesting 3 part article by Vasily Zubarev at dpreview on Computational Photography (CP). CP means many things, involves all aspects from sensors to optics to signal processing..

From the article, “Everywhere, including Wikipedia, you get a definition like this: computational photography is a digital image capture and processing techniques that use digital computation instead of optical processes. Stanford Professor and pioneer of computational photography Marc Levoy (he was also behind many of the innovations in Google’s Pixel cameras) gives another definition – computational imaging techniques enhance or extend the capabilities of digital photography in which the output is an ordinary photograph, but one that could not have been taken by a traditional camera.” …

He concludes..

“Throughout history, each human technology becomes more advanced as soon as it stops copying living organisms. Today, it is hard to imagine a car with joints and muscles instead of wheels. Planes with fixed wings fly 800+ km/h — birds don’t even try. There are no analogs to the computer processor in nature at all.

The most exciting part of the list is what’s not in it. Camera sensors. We still haven’t figured out anything better than imitating the eye structure; the same crystalline lens and a set of RGGB-cones like the retina has.

Computational photography has added a “brain” to this process. A processor that handles visual information not only by reading pixels through the optic nerve but also by complementing the picture based on its experience. Yes, it opens up a lot of possibilities for us today, but there is a hunch we’re still trying to wave with hand-made wings instead of inventing a plane. One that will leave behind all these shutters, apertures, and Bayer filters.

The beauty of the situation is that we can’t even imagine today what it’s going to be….”

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