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> produce full-color images that are equal in quality to those produced by conventional cameras I was really skeptical of this since the article conveniently d
by bhaney 2y ago
> produce full-color images that are equal in quality to those produced by conventional cameras
I was really skeptical of this since the article conveniently doesn't include any photos taken by the nano-camera, but there are examples [1] in the original paper that are pretty impressive.
[1] https://www.nature.com/articles/s41467-021-26443-0/figures/2 https://www.nature.com/articles/s41467-021-26443-0/figures/2
- andrepd 2y agoHow does this work? If it's just reconstructing the images with nn, a la Samsung pasting a picture of the moon when it detected a white disc on the image, it's not very impressive.
- nateroling 2y agoI had the same thought, but it sounds like this operates at a much lower level than that kind of thing: > Then, a physics-based neural network was used to process the images captured by the meta-optics camera. Because the neural network was trained on metasurface physics, it can remove aberrations produced by the camera.
- Intralexical 2y agoI'd like to see some examples showing how it does when taking a picture of completely random fractal noise. That should show it's not just trained to reconstruct known image patterns. Generally it's probably wise to be skeptical of anything that appears to get around the diffraction limit.
- brookst 2y agoI believe the claim is that the NN is trained to reconstruct pixels, not images. As in so many areas, the diffraction limit is probabalistic so combining information from multiple overlapping samples and NNs trained on known diffracted -> accurate pairs may well recover information. You’re right that it might fail on noise with resolution fine enough to break assumptions from the NN training set. But that’s not a super common application for cameras, and traditional cameras have their own limitations. Not saying we shouldn’t be skeptical, just that there is a plausible mechanism here.
- neom 2y agowe've had very good chromatic aberration correction since I got a degree in imaging technology and that was over 20 years ago so I'd imagine it's not particularly difficult for name your flavour of ML.
- Intralexical 2y agoMy concern would be that if it can't produce accurate results on a random noise test, then how do we trust that it actually produces accurate results (as opposed to merely plausible results) on normal images? Multilevel fractal noise specifically would give an indication of how fine you can go.
- brookst 2y ago"Accurate results" gets you into the "what even is a photo" territory. Do today's cameras, with their huge technology stack, produce accurate results? With sharpening and color correction and all of that, probably not. I agree that measuring against such a test would be interesting, but I'm not sure it's possible or desirable for any camera tech to produce an objectively "true" pixel by pixel value. This new approach may fail/cheat in different ways, which is interesting but not disqualifying to me.
- Intralexical 2y ago> Ultrathin meta-optics utilize subwavelength nano-antennas to modulate incident light with greater design freedom and space-bandwidth product over conventional diffractive optical elements (DOEs). Is this basically a visible-wavelength beamsteering phased array?
- itishappy 2y agoYup. It's also passive. The nanostructures act like delay lines.
- mrec 2y agoInteresting. This idea appears pretty much exactly at the end of Bob Shaw's 1972 SFnal collection Other Days, Other Eyes. The starting premise is the invention of "slow glass" that looks like an irrelevant gimmick but ends up revolutionizing all sorts of things, and the final bits envisage a disturbing surveillance society with these tiny passive cameras spread everywhere. It's a good read; I don't think the extrapolation of one technical advance has ever been done better.
- walterbell 2y agoThanks for the recommendation. https://news.ycombinator.com/item?id=42217251 https://news.ycombinator.com/item?id=42217251
- KWxIUElW8Xt0tD9 2y agoI have been wondering where I read this story for some time now -- thanks.
- roelschroeven 2y agoThose images are certainly impressive, but I certainly don't agree with the statement "equal in quality to those produced by conventional cameras": they're quite obviously lacking in sharpness and color.
- neom 2y agoconventional ultra thin lens cameras are mostly endoscopes, so it's up against this: https://www.endoscopy-campus.com/wp-content/uploads/Neuroendokrine-Tumoren-im-Magen-NET-Abb-1a.jpg https://www.endoscopy-campus.com/wp-content/uploads/Neuroend...
- jvanderbot 2y agoJust curious, what am I looking at here?
- neom 2y agomy education is on the imaging side not the medical side but I believe this: https://www.mayoclinic.org/diseases-conditions/neuroendocrine-tumors/symptoms-causes/syc-20354132 https://www.mayoclinic.org/diseases-conditions/neuroendocrin... + this: https://emedicine.medscape.com/article/176036-overview?form=fpf https://emedicine.medscape.com/article/176036-overview?form=... - looks like it was shot with this: https://vet-trade.eu/enteroscope/218-olympus-enteroscope-sif-q260.html https://vet-trade.eu/enteroscope/218-olympus-enteroscope-sif...
- dylan604 2y agoThere's one of those Taboola type ads going around with a similar image that suggests it is a close up of belly fat. Given the source and their propensity for using images unrelated to topic, so not sure if that's what it really is.
- atahanacar 2y agoInside of a stomach basically. A polypoid lesion, which I can't tell apart the exact diagnosis but the filename suggests is a neuroendocrine tumor.
- baxtr 2y agoAlso interesting: the paper is from 2021.