What’s that noise? Part one: Shedding some light on the sources of noise

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How would you react if I told you that the aperture and shutter speed you choose make more difference to image noise than the ISO setting? You might be surprised to discover that a lot of the noise in your images doesn’t come from your camera at all: it comes from the light you’re capturing.

To really understand what’s going on in your camera and, hence, how to get the best results out of it, it helps to understand a little bit about where noise comes from. Noise is widely misunderstood and yet it lies at the heart of most technical assessments of image quality and camera capability.

In simple terms, noise is any variation from the true ‘signal’ that you’re trying to capture. Visually it’s immediately recognizable as pixels of unexpected brightness or color, most easily seen in areas where you might otherwise expect a smooth result. The first thing to realize is that there are several mechanisms that contribute towards noise and that all of them can play a different role, even within a single image.

In this multi-part article, we’re going to look at two major sources of noise: shot noise and electronic noise, and what they mean for the way you shoot. And because this first source of noise is so significant, we’re not going to talk about electronic noise at all in this first part. By the end of both parts you should understand where noise comes from, where the strengths of your camera lie, and hence how to get the best out of it (and when it’s likely to let you down).

Shot noise

Probably the most significant and certainly least recognized source of noise is what we call ‘shot noise’ or ‘photon shot noise’. In the simplest terms, this is you being able to see the impact of light’s inherent randomness.

You might remember talk of photons from science classes, and the key thing to remember is that, although we perceive light as being pretty uniform, it actually travels as a series of packets. That is: light is quantized. These packets (photons) arrive at your eye or your camera sensor at random intervals. Because of the way the eye and the brain work, you don’t notice this, but when you look at a scene, you’re being bombarded by little packets of randomly occurring light from every part of that scene.

‘So what?’ you might say. Well, let’s try a little thought experiment. Rain is also a series of discrete packets, that fall randomly over time, so it makes a fairly robust metaphor for the way light behaves. So let’s see what happens if we imagine trying to measure rain, using a series of test tubes.

Stand outside in the rain, with your group of test tubes covered with a plastic card. Remove the card for a fraction of a second, then quickly put it back over the tubes. You probably wouldn’t be at all surprised to find no raindrops in one tube, two in another and one in the other two tubes because, just like light, raindrops occur randomly. Try the experiment again and leave the tubes exposed for a longer period of time: now you’ll find all your test tubes are nearly full. If you tried measuring in detail, you might find that you had 420 drops in one tube, 380 in another and 400 in the other two tubes, but generally, you’d probably look at them and conclude they’re all pretty much the same.

This randomness, even though it’s raining similarly hard over all the test tubes, is noise: it’s variation from the underlying signal.

An important thing to know is that, although the absolute differences in raindrops collected are larger for the longer exposure (it’s a difference of 20 raindrops!), it only accounts for a small proportion of the total number (+/- 5%). With the very short exposure to the rain, the differences were only +/- 1 raindrop between test tubes, but proportionately it made a huge difference (+/- 100%). Or, to use the correct terminology, the signal you captured in the short exposure was small, relative to the amount of noise you experienced: you had much lower signal-to-noise ratio.

This is exactly how shot noise contributes to your photographs. A darker exposure gives you less chance to catch photons, so you’re more likely to be able to see the random nature of them hitting your pixels. And this doesn’t just apply to bright or dark exposures, it also applies to bright and dark areas within the same image. Bright parts of the image are made up from more photons hitting them during the exposure, so it’s harder to perceive any variance between neighboring pixels whereas, in the darker parts of the image, fewer photons hit your sensor, so you’re more likely to be able to see the underlying randomness.

The important thing to realize is that this type of noise is present whenever you try to capture light. Whether you use film or digital, medium format or a smartphone, all of the light you’re capturing has shot noise built into it. And the solution is always the same: the more light you are able to capture, the less you’ll be able to see that noise.

 

The effect of exposure on noise

 

 

Understanding the sources and effects of noise in your final image requires a good understanding of the process of capturing light and the steps it passes through on the way to your final image. The diagrams below show an image of a scene you might want to photograph, with the stripe just below the image showing the scene brightness. The light blue dots within this stripe represent the shot noise that you might experience: there are fewer of them at the dark end of the wedge, but they’re more visible.

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