Noise in imaging chains: correlations and predictions

Noise is an important factor in image quality. We analyze it in images produced by digital cameras. We show that, beyond the usual standard deviation measurement, spatial correlations also convey interesting information which allows to (i) better describe the perception of the noise, (ii) analyze an unknown imaging chain. Indeed, knowledge of these spatial correlations is necessary to predict the noise after the rescaling and sampling involved in a realistic imaging chains.