I'm trying to understand the behavior of my DSLR camera sensor (Canon 80D). I've taken a picture of a gradient from top-right to bottom-left corners of a square. This square is positioned at the right-hand side of the picture, so that it'd be easy to just take the diagonal, starting from the top-right corner, that would be composed only of green-filtered photosites.
The shot is done with a defocused lens, so that the detail of the monitor pixels pattern couldn't cause any interference like moire. ISO sensitivity is set to the smallest value: 100, exposure is 1/10 s, and aperture is f/3.2, with f=24 mm.
What I get is that as the intensity registered by a photosite increases, the noise amplitude also increases. See this plot of the raw data of the diagonal, taken from the CR2 file:
The fact that noise amplitude is correlated with signal amplitude makes me wonder. Thermal noise should be the same on all the photosites, regardless of their illuminance. Quantization noise wouldn't even be noticeable on this scale of ~10000 counts (and it's also additive). Shot noise also shouldn't be noticeable at this illuminance.
So what is the origin of this multiplicative noise then?
I've done some more captures to find the relation between the mean and the variance of the pixel values. I've taken 15 shots of a gray gradient, used every 50th row and column of the resulting data, and computed mean and variance in the sets of 15 values for each resulting pixel.
Here are the results. Blue the variance, orange the least-squares fit:
The plot above smoothed with moving average with 100 points in the window:
Is this consistent with the shot noise explanation given in the answers?
After some more comments I've subtracted the DC offset of about 511.9 from all the pixels, and now the smoothed ratio of variance to mean (i.e. estimated gain) as a function of mean looks like this:
So, now the answer that explains the noise as the shot noise makes sense.