![]() As above, shot noise goes as the square root of exposure, and if you set exposure according to the meter, exposure will be inversely proportional to ISO, which means that the SNR will be inversely proportional to the square root of ISO. It only appears to be linked with ISO because you will generally set a smaller exposure as you raise the ISO. So, shot noise depends on exposure, not ISO. This is a 'fixed pattern noise' and is generally removed almost completely in image processing. The latter is the effects of pixels not being completely the same, and responding slightly differently. The former is the effect of the electronic noise (in fact, mostly not from the sensor itself but from the electronics which process the sensor output) and is generally only visible in the deep shadows at reasonable exposures. The other two are called 'read noise' and 'photo response non-uniformity'. This noise gives a signal to noise ratio which depends on the square root of the amount of light energy captured in the photo, which for a given sensor size is proportional to exposure. The most important one is called 'photon shot noise', which comes from the structure of the light itself, not the sensor. There are three major components of that noise. Firstly, very little of the noise that you see in digital cameras is 'sensor noise'. Unfortunately it is a common one, because there are many web explainers which frankly are nonsense. This question seems to be based on a mixed-up notion of the noise sources in digital photography. Is sensor noise monotonically increasing with ISO, or is there a low noise plateau (a flat minimum area) and then the noise increases with increasing ISO? What do you mean by "sweet spot" in this context? To see if there is a "sweet spot" in the ISO curve? ![]() For this you'd need a way to produce an image of supposedly uniform exposure and tool that could read individual pixel values and perform computations on the set of values. One could measure noise by measuring the variation in individual pixel values of an image of a supposedly constant lightness. Is there a way for a consumer to measure sensor noise vs. The largest portion of noise in most digital images doesn't depend directly on the ISO setting, but rather on the product of exposure (the density of light falling on the sensor), sensor surface area and sensor quantum efficiency. Another small portion may be proportional to ISO setting. Some (usually a small portion of the total) may be constant, meaning they decrease relative to increased ISO setting. There are many sources of noise in a digital image. Monotonically increasing with ISO, or is there a low noise plateau (a flat minimum area) and then the noise increases with increasing ISO? because you believe that all noise in a digital image is caused by or at the sensor?, or.to distinguish certain noise from other noise found in a digital image? If so, how do you characterize this noise that you are trying to distinguish from other noises?) or.
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