Deep-Tech Swiss Startup is Bringing Quantum Physics into Image Compression

                                             Image by monicore from Pixabay

To See The Ordinary

I’m not a very good photographer, though I appreciate a well-taken photo just like anyone with an artistic bent.

“It takes a lot of imagination to be a good photographer. You need less imagination to be a painter, because you can invent things. But in photography everything is so ordinary; it takes a lot of looking before you learn to see the ordinary.”

— David Bailey

The above quote from the famous British photographer David Bailey is correct in its estimation that it’s not easy being a good photographer, but there is technology out there that can make the pictures you take look better.

Image compression — minimizing the size of the bytes of your graphic files that do not lower the quality of the photo — is one cure-all to turn you into, at least in a little way, a faux David Bailey.

The most common ways to compress these days on the internet are with graphic image formats JPEG and GIF, though fractals and wavelets are other methods used for image compression.

And you may be asking why TQD is talking about all the technicalities of image compression when our focus should be all things quantum?

Well, because of Dotphoton™, that’s why. Dotphoton is a Swiss-based deep-tech startup that manufactures “lossless raw image compression” solutions for biomedical, aerial, automotive, life sciences, and Earth observation sectors based on the startup’s quantum information research high compression ratios at the University of Geneva.

Bringing quantum physics into image compression

— Dotphoton™

Dotphoton™

Founded as a University of Geneva spinoff in 2018 by CEO Eugenia Balysheva and CTO Bruno Sanguinetti — who lead an expert team of physicists, computer scientists, entrepreneurs, and creatives — Dotphoton’s core technology is the Jetraw for biotech imagery and Dotphoton Core targeted to camera manufacturers.

Jetraw features include a 5–10× compression ratio and promises to reduce storage costs by — 80% while the Dotphoton product, meanwhile, can significantly “improve the performance of your camera and make raw image acquisition and processing up to 10 times faster”.

All this wouldn’t be possible without cash, and luckily Dotphoton has this in the form of grants, Non-Equity Assistance and a seven-digit Pre-Series A round last year from Swiss private investors.

 

On the round, Dotphoton’s CEO, Eugenia Balysheva, commented: “We are grateful to our new and existing investors for sharing Dotphoton’s vision and for helping us to build a secure and strong company. The newly raised funds will help to scale Dotphoton’s image compression solutions and meet rising demand from the new customers.”

A former senior researcher in quantum physics at the University of Geneva, CTO Bruno Sanguinetti’s technical skills counterbalance Balysheva’s business acumen and can set the scene where Dotphoton’s core technology — already validated by major Swiss research centres — moves to a new level of commercialization and success.

James Dargan
James Dargan
James Dargan is a contributor at The Quantum Daily. His focus is on the QC startup ecosystem and he writes articles on the space that have a tone accessible to the average reader

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1 Comment

  1. Hi,
    Many thanks for the article. I have recently met several pieces of text dedicated to the Dotphoton image compression solution. However, general and often very strong claims such as “lossless raw image compression” that are found in these articles are not supported by any solid argument. Why, what the company offers is superior to what wavelet-based image compression techniques such as SPIHT, EQ, LS-EQ to name a few can achieve (I have mentioned here lossy compression techniques since the Dotphoton solution in my humble opinion does not belong to the class of lossless compression methods)? How the obtained “quantum”-based results agree with the rate-distortion theory? It would be good if such questions. It would be great if such answers will be given.

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