# Why doesn't noise depend on exposure time?

In the post Why do cameras use a single exposure rather than integrating across many very quick reads? an important question was if the noise depends on the exposure time or not. By noise I mean the absolute noise (N), not the relative noise (S/N). I was convinced about this correlation because I was thinking that the noise is accumulated during the exposure time, so if it is longer the noise would be higher.

To test this hypothesis I tried to shoot black images with the lens cap on the lenses, in such a way to have S=0. I am using Canon 600D, ISO100 and f/3.5

I wrote a python script to compute the mean value averaging over all the pixel with a simple mean or with a quadratic mean (sqrt(sum_i (R_i^2)) where R_i is the ith-pixel considering only the red channel.

I used jpeg, because I'm not able to read raw from python. Using jpeg the resolution of the noise is quite small (1/256), but I have obtained interesting results.

Here the plot: on the y-axis the noise, on the x-axis the exposure time.  it seems that the noise is quite constant up to exposure of 1s, then it start to increase

I have also tried to shot with ISO3200, here the results:  as expected the noise is much bigger (~10 times) but the behaviour with exposure time is similar (probably it raise a bit faster).

Why this behaviour?

Why is the green channel more noisy?