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Cutting edge cell phone camera performance is absolutely mad. I did a side-by-side comparison of a Micro Four Thirds camera (4/3" sensor) and an iPhone SE (1/3

Cutting edge cell phone camera performance is absolutely mad. I did a side-by-side comparison of a Micro Four Thirds camera (4/3" sensor) and an iPhone SE (1/3" sensor) and the performance was... pretty much the same. And I'm not talking about some ML interpolation wizardry or automatic face beautification; I was photographing barcodes and testing how many were readable in the resulting images - hardly something Apple would have specially optimised for. The iPhone has a much smaller sensor, a much smaller lens, costs less, and manages to pack in a bunch of non-camera features. To be competitive in the modern cell phone market your camera has to be straight up magic.

dan_quixote 5y ago
It actually wouldn't surprise me if they optimized for bar/qr code readability. I wrote something years ago that used industrial cameras to read QR codes as well as very precise metrology features. I had to optimize the optical/lighting setup for the feature measurement and then wrote some finely-tuned operations to identify the QR code, window down to the code only, clean up edges/features with expensive convolutions (mostly median filter) and then finally read the code. None of this was visible to the operator, but if you saw the final image of the QR code it was essentially binary color space and looked a bit cartoon-like.
- michaelt 5y ago
  They might have some optimisation for photographing documents, it's true. But when I say the performance is good, I'm not just declaring the images good because the portraits have simulated bokeh, or face-detecting autoexposure, or image stabilisation, or tasteful HDR, or a beauty mode that airbrushes out blemishes and makes photos of sunsets really pop. Even in applications where none of those features come into play, the iPhone, can still go toe-to-toe with cameras with much larger sensors.
dcz_self 5y ago
Did you do your tests in good lighting? Did you compare raw sensor output, or post-processed? Big sensors capture more light and have more bokeh. With enough light, the first doesn't matter, and bokeh is not a thing for QR codes. If you didn't have enough light, then it's probably the question of how denoising was done, and what details have been guessed by fancy algorithms. Geometrical shapes are easy to guess, but when I look at pictures of landscapes, they typically devolve into a painting after 1000×1000px if taken on a phone.

dan_quixote 5y ago

It actually wouldn't surprise me if they optimized for bar/qr code readability. I wrote something years ago that used industrial cameras to read QR codes as well as very precise metrology features. I had to optimize the optical/lighting setup for the feature measurement and then wrote some finely-tuned operations to identify the QR code, window down to the code only, clean up edges/features with expensive convolutions (mostly median filter) and then finally read the code. None of this was visible to the operator, but if you saw the final image of the QR code it was essentially binary color space and looked a bit cartoon-like.

michaelt 5y ago
They might have some optimisation for photographing documents, it's true. But when I say the performance is good, I'm not just declaring the images good because the portraits have simulated bokeh, or face-detecting autoexposure, or image stabilisation, or tasteful HDR, or a beauty mode that airbrushes out blemishes and makes photos of sunsets really pop. Even in applications where none of those features come into play, the iPhone, can still go toe-to-toe with cameras with much larger sensors.

dcz_self 5y ago

Did you do your tests in good lighting? Did you compare raw sensor output, or post-processed? Big sensors capture more light and have more bokeh. With enough light, the first doesn't matter, and bokeh is not a thing for QR codes. If you didn't have enough light, then it's probably the question of how denoising was done, and what details have been guessed by fancy algorithms. Geometrical shapes are easy to guess, but when I look at pictures of landscapes, they typically devolve into a painting after 1000×1000px if taken on a phone.