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Comment by boxcardavin | Hacker News Reader

One should remember that writing camera software that is agnostic to the hardware is technically hard, and nearly impossible if you want gorgeous photos (a la iPhone). When taking astronomy images we would characterize the CCD (mostly for noise) each night, and you need that kind of approach to tune your software to your hardware.

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> One should remember that writing camera software that is agnostic to the hardware is technically hard

In this case, is it?

Their solution involves using burst mode, then taking those many pictures and turning them into 1 high quality image. Burst mode would simply output a bunch of .jpg images... couldn't you run the algorithm on those standardized images?

You get called dark current (thermal noise) on CMOS and CCD sensors, and the signal-to-noise ratio goes down as you decrease the exposure time. You see the effect when taking a low light photo, the graininess is from the SNR being very low while the noise is showing through. You can smooth this out quite a bit by combining burst photos (see Cortex Camera app) as the noise is random, but you always get better results with more light for each exposure.

Considering the many advantages to shooting in RAW, it is safe to assume that all one-size-fits-all software processing (a la iPhone) are vastly inferior to performing the image processing manually (with the data directly off the censor, uncompressed, and unaltered)

Would this be the end user doing that? Although you can't raw out of an iPhone it's not one-size-fits-all, I'd say it's the opposite as they have tuned the processing for that exact sensor/lens combination after testing.

To be clear, I would LOVE to get raw out of an iOS device camera. It would make motion analysis much more precise. With iOS 8 you have kinda/sorta control over the exposure time, but it could be more precise.

My understanding is that most flagship camera sensors are made by Sony, so there may be less diversity of hardware than there appears to be.

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