Well, a phone can reconstruct this license plate, and in fact any license plate in lieu of this one! And invent a new one!
Which is worrisome for justice. Presenting proof, that was uploaded to servers, horodated and geostamped, won’t be enough in a court of law. Anyone can answer: “What if the iPhone recreated and inferred the presence of a knife using the neural engine? This face, is it real? The distance, is it repositionned?”
Deepfakes, robocalls and Caller ID and voice impersonation, automatic ML in photos, if this train keeps going, we won't know what's real at all. I am struggling to see how we will function.
That's where we started, in a way. Perhaps our short time of feeling we had a grip on reality will just have been a passing phase, before returning to normality.
but now we have all these artificial experiences that might clock real to the senses and have a reputation of fidelity, yet have always been editable and are increasingly made of black box constructive interpretations that value who-knows-what over fidelity. and no part of the process can be interrogated for motivations or detail.
He said they went through hours of details on how the various enhancement algorithms and systems worked, and at the end, the bottom line was basically 'take a better picture in the first place' - as in get the lens, lighting, and parameters right in the first place, and that'll be the biggest factor in how far the processing HW/SW/people can take the enhancements.
Maybe the new software with huge R&D budgets is now better, but I'd suspect this advice is still not obsolete...
It is good advice indeed.
Still, it's amazing how processing has evolved. I took a picture of my 3yo daughter having finally fallen asleep after a bout of night terrors, in the dark light (using a Hue Ambiance in her room; best things ever) - in the S21 Ultra viewfinder I could see absolutely nothing, however after 3 seconds of a steady hand I was rewarded with a fantastic picture better lit than what my eyes had adjusted to.
(If I had any complaints, it would be that I'd like it to be darker - however I can understand why on average most would like the processed result.)
Guessing what stops you is that the Apple team that makes camera software has a budget that makes the Nikon pc app team look quite small.
The processor still doesn't have access to said "real dof", which is the point of this comment thread.
Also, because phone cameras have gotten so good, the skill floor for what you’re talking about is higher. There’s more skill involved in using software like lightroom than you might think. I’m a hobbyist photographer, and sometimes my iphone just seems more skillful than I am using my nicer camera and Lightroom.
DSLR and mirrorless cameras have better optical properties. But they are held back by starting too late and being much worse when it comes to software. These cameras also are limited by their CPUs, which are a decade behind, and by their batteries, which are much smaller but expected to last for thousands of exposures.
I mean, sure, but the A15 bionic is much more power constrained and effectively has less 'GPUs' and cores than the M1, likely because the SoC is also constrained by its size within the phone housing.
My Corsair H150i Pro AIO water cooler and decent airflow case (Define 7 W/Corsair ML140s) allows me to run my Ryzen 3900XT at 4.4ghz constantly, all cores, for any kind of real life workload.
Good luck trying that with a laptop.
Hell, one of the major selling points of the most recent iphones is prores recording! Dump half a second of that into a file. If that means a half-full phone can only fit a thousand photos before it's emptied, then sure I'll take it.
Correct me if I'm wrong but there's still a huge issue with silicon processing capabilities/power when it comes to image sensors (which is why camera sensors buffer images between shots). I unfortunately don't remember the context but it said something that it was (very far) from possible to actually get all the sensor data into the processor and as a result you only take a small fraction of the actual incident light/photos practically.
Most of it ends up in a RAM-like write buffer, because SD cards, or even faster formats like CF-express, can’t keep up with the write speed of tens of 50 megapixel shots coming through every second.
There are sensor readout speed limits, which is why you don’t see cameras exceed 30 frames per second of 8k recording, but there’s no reason why you couldn’t read out the entire full-well capacity of the sensor each of those frames.
And I am wrong. Depending on the phone.
A Nikon battery: 2280 mAh.
An iPhone 13: anywhere from 2406–4352 mAH.
Yeah, that’s a way smaller power budget than a Pro iPhone, especially as you have autofocus and image stabilization systems that have to move around a lot more mass.
(And as a digital camera user - at least I can hot swap batteries. I miss my old cell phones that allowed for this.)
The screen is off except when I'm previewing a photo. The viewfinder is physical. The metering is only on for 10-20 seconds after I wake the camera by touching the shutter release and is only displaying on a low power monochromatic LCD. Autofocus only happens while I'm holding the shutter release until it finds focus then locks.
Meanwhile the iPhone battery is powering what is, effectively, an entire laptop with a 5+" screen and cellular, wifi and bluetooth radios.
Articles I can find are quoting an iPhone taking a few hundred shots on a charge. Nikon's testing puts my camera able to take a few _thousand_ per charge. There's literally an order of magnitude difference from my Nikon's 1400mAh battery to a iPhone's 2500-4500mAh battery. Two to three times the capacity for 1/10 the pictures.
They also take a second or so to wake from standby which is super annoying for my job, so I have it set to 5 minutes. That essentially means it never goes in to standby on a wedding day.
Closely related: "It's impossible to just 'enhance' an image to make a license plate readable. Lost information ist lost". This was big due to some US TV show at the time, I guess. Here, the error was in the assumption that the information was lost: as it turns out, there's a wide space of possibilities for image quality to be too low for us to easily read some letters, but good enough to contain the clues allowing a smart algorithm to reconstruct them.