I haven't seen Ironman so don't get the reference, but basically most things can be solved by a brute force method. Capture as much data as you can, then pick out the bits you really want. I was thinking of keeping within the visible spectrum here. There would of course still be physical limits. I'm not expecting a movie style "enhance that" and be able to pick off someone's fingerprint on a glass via a reflection off some other surface!
On that note, I would see value in some radical sensor which captures spectra at each detector. To be fair, this is probably overkill for "normal" photography, but it would have massive uses in science. The nearest to that I've seen is a sensor which expands the bayer concept, and you have a colour filter array with lots more passbands, at the cost of overall spatial resolution.
I do see the possible advantages of Foveon type sensors, but they aren't keeping up with the bayer behemoth. Sigma were too late to the party. The Merrill era came too late by which point they lost most of their potential advantage over bayer sensors. I have long disliked the bayer sensor concept as a fair chunck of what I do doesn't play well with the colour sampling assumptions involved. Going back to my 1st point, the massive increases in MP count have somewhat negated the need for Foveon, by providing higher spatial sampling rates. Of course, an equivalent output pixel Foveon would still have the advantage, but development of it doesn't seem to be going anywhere. You have to take off the general photography hat, and think of this as sampled data manipulation. Increasing MP counts far beyond what we have right now helps a lot in that respect. I would also have to add not every pixel needs to look perfect all the time and there is some tradeoff to be made there.
I think we are closer to moving towards computational photography. That is, get data by whatever sources available and work out the image from that. Didn't someone make a smartphone with two or more sensors in it for example? I've even wondered if something like interferometry might be a future development to increase visible imaging potential in smaller form factors. I'm not holding my breath for consumer level aperture synthesis to be available any time soon.
On that note, I would see value in some radical sensor which captures spectra at each detector. To be fair, this is probably overkill for "normal" photography, but it would have massive uses in science. The nearest to that I've seen is a sensor which expands the bayer concept, and you have a colour filter array with lots more passbands, at the cost of overall spatial resolution.
I do see the possible advantages of Foveon type sensors, but they aren't keeping up with the bayer behemoth. Sigma were too late to the party. The Merrill era came too late by which point they lost most of their potential advantage over bayer sensors. I have long disliked the bayer sensor concept as a fair chunck of what I do doesn't play well with the colour sampling assumptions involved. Going back to my 1st point, the massive increases in MP count have somewhat negated the need for Foveon, by providing higher spatial sampling rates. Of course, an equivalent output pixel Foveon would still have the advantage, but development of it doesn't seem to be going anywhere. You have to take off the general photography hat, and think of this as sampled data manipulation. Increasing MP counts far beyond what we have right now helps a lot in that respect. I would also have to add not every pixel needs to look perfect all the time and there is some tradeoff to be made there.
I think we are closer to moving towards computational photography. That is, get data by whatever sources available and work out the image from that. Didn't someone make a smartphone with two or more sensors in it for example? I've even wondered if something like interferometry might be a future development to increase visible imaging potential in smaller form factors. I'm not holding my breath for consumer level aperture synthesis to be available any time soon.
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