Reduction of Noise in Astronomical CCD Images

Noise is caused by quantum (random) variations in the electric charge of each CCD pixel (photosite) leading to grainy or speckled images. Here we look at ways to minimise the effect.


The number of unwanted electrons generated inside a CCD can be minimised by keeping it cool. Purpose-built astronomical CCD's are usually mounted on a cooling device, and noise from these CCD's can often be ignored. Un-cooled cameras, ordinary digital cameras and webcams usually generate quite a lot of noise. Some people put their webcams in the freezer prior to using them, but beware of condensation!

The message is - if you can afford it buy a cooled camera!

Long Exposure

Long exposures will give time for the light from the target celestial object to build up a strong charge relative to the noise. How long is 'long' will very much depend on the magnitude of the subject and the type of camera.

However, long exposures have their own problems:

  • The brighter stars may overexpose (saturate) their pixels causing distortion.
  • Imperfections in telescope tracking can cause fuzziness or streaks.
  • Dark current may accumulate (with its own noise) to an unacceptable level.

For ordinary digital cameras and modified (long exposure) webcams a lot of noise can be generated and there is a limit to how long the exposure can continue before the whole image is 'fuzzed out'. You will need to experiment to find out the optimum  exposure. Unmodified webcams should be run with minimum 'gain' as the amplifiers used to magnify their output introduce even more noise. I normally run my Toucam at 5 or 10 frames per second and set the gain to as low as possible.

With a cooled camera you should make the exposure as long as possible up to the point where poor tracking begins to fuzz the image or bright objects become overexposed. 


Noise can be reduced by stacking (averaging) multiple images. The amount of noise is reduced by a factor that is the square root of the number of images averaged.

  • Average 4 images - noise halved
  • Average 100 images - noise reduced to 1/10th

This is where webcams benefit. Hundreds of video frames can be stacked to reduce noise, (even though the webcam is quite noisy in each individual frame).

In practice with my MX5C and DSI cameras I use exposures of up to 120seconds, but this means I have to spend quite a bit of time to ensure the tracking is good. I would try to collect 30-40 good images then stack them using Registax or Maxim DL.

With the webcam I would generally take videos of 2minutes at 5 or 10 frames per second and using the minimum gain possible. The video is stacked using Registax.

If some of your images have CR hits or other unwanted defects then you could try stacking using the Median method. This does not reduce quantum noise quite so much but it can reduce other defects more effectively than "average"


Having obtained the best possible images from optimum exposure, calibration and stacking multiple images, the result can often be improved by  filters provided in your image processing software. Different software products use different names for filters, but the two basic ones are:

  • Low Pass (FFT) Filter
Works by reducing the high-frequency (fine detail) components of the image. In effect this smoothes the image making noise less visible but at the expense of loss of detail or sharpness. This is often fine for a nebula or galaxy images but not so good if you are trying to get crisp clear lunar landscapes.
  • Median Filter
Works by replacing the value of each pixel by the median of the values of the pixels around it. This can be quite effective at removing noise while maintaining a reasonable level of sharpness.

Image processing software often has special noise reduction filters. PSP's 'edge preserving smooth' is one of my favourites. It is quite good at smoothing a nebula while maintaining the sharpness of stars.  Recent versions of PSP have a digital noise removal tool and Photoshop has a similar facility. Astroart provides the ability to view and edit an FFT transformation of the image and this can be useful in detecting and correcting noise. The software package Neat Image has advanced noise reduction capability and I use it quite often.

It is worth trying out several different noise reduction filters on an image to see which works best.

Noise Reduction Strategy

My strategy is:

Webcam: Use the lowest gain possible. Capture at least 600 frames. Stack only frames that are reasonably good. It is really worth the effort to examine each frame of the video and select/deselect it rather than relying on the software to select the best 'quality' frames. The automatic 'quality' functions rely on a measure of image contrast but can include frames that have a lot of shape-distortion in them.

Do not over-do the wavelet filtering (or other sharpening filter) as this can accentuate the noise. Use PSP's 'digital noise removal' or Neat Image on the resulting image.

MX5-C/DSI: Use exposure sufficient to capture a reasonable image without over exposing individual stars or causing tracking problems. In practice this means up to about 120secs per image with my equipment. Capture at least 10 images, but 30 or 40 is better. Calibrate with dark frames, colour convert (for MX5-C) then stack (average) the images. Experiment with median filter, 'edge preserving smooth' and Neat Image to see which gives the best result. It may be worth applying a median filter or FFT-Lowpass to each individual exposed image before stacking.

There is often a trade-off between image sharpness and noise. Using an UnSharp or Deconvolution filter to improve detail will tend to accentuate noise. Several repetitions of  moderate sharpening/de-noising may work better than a single pass through each filter.

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