Image Noise: The Ultimate Guide to Image Noise

Image noise can make photographs and scanned images flecked, grainy, and hard to edit with. In this ultimate guide, learn more about the different types of image noise and how to correct for it both while you take photos and during editing.

What is image noise?

Image noise is a defect in images such as photographs and scanned images. The "noise" is small dots or pixels of miscolored or overly bright colors overlaid on an image. Image noise is generally caused by electronic noise, or electronic interference that stops the sensor from fully recognizing every detail of an image. Film can also pick up traces of image noise.

Image noise varies in intensity from occasional specks of interference that allow the vast majority of the image to be perceived to image noise that completely overwhelms the image and allows for little to no information transfer. However, this severity of image noise is usually reserved for astronomical images.

While image noise is typically regarded as a defect that photographers and graphic designers want to remove, that's not always the case. Some types of noise are enjoyed because of the retro or artistic appeal they add to the photo; artificial filters of image noise can also be purposefully layered onto an otherwise clean image. However, even in case where graphic designers want picturesque image noise, the original noise might first be removed for more image control.

Some of the most common types of image noise include:

  • Film grain: This noise is isotropic and hard to predict, creating dark silver grains in the image. This is more likely to develop in film with silver halide grains.
  • Gaussian noise: Gaussian noise is caused in digital image sensors. Blue patches of an image are more likely to have amplified electronic noise.
  • Periodic noise: This noise occurs because of electrical interference. The best way to remove this type of interference is when the image is being taken, but this can also interfere with the capture of image details.
  • Quantization noise: This uniform noise happens across an image during scanning.
  • Salt-and-pepper noise: This impulsive noise has black or dark specks in light areas and light specks of noise in darker areas.
  • Shot noise: Photon shot noise is caused by changes in how the sensor senses photons during exposure.

How to remove noise from an image

There are lots of different tools available for photographers and graphic designers to remove noise from their images.

One of the most popular tools is a smoothing filter. This tool averages or "smooths" pixel intensity across adjacent pixels to remove specks that have strongly contrasting intensity. However, this effectively blurs the image on a small level, obscuring some fine details and intensity contrast that should exist. Modern tools can better recognize when strong contrasts should occur in order to both preserve the original image and correct defects. High-quality graphic design programs will offer noise reduction tools you can fine-tune and control.

You can also reduce the risk of noise before the image is taken in the first place. To do that, photographers can:

  • Determine the right exposure and ISO settings for the picture. Typically, low ISO and short exposure times will create images with the least amount of noise.
  • Use a large aperture.
  • If possible, use a full-frame sensor camera since that will allow more light into the image to reduce noise.

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