After stacking 6 photos, the leftovers of the astronaut are even fainter.

This means you cannot simply point the camera at the sky and snap away.

In astrophotography you cannot avoid post processing your images, so stacking and editing your images serves three main purposes: Reduce noise and deal with light gradients and vignetting.

Image stacking is the technique used to improve the signal to noise ratio, and it is the only noise reduction method that will boost the image details rather than smear them out.

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In this article, we will discuss some of the most popular software available for astrophotography image stacking.

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Note: Dont miss the detailed video at the end of this article, It was created to help show you how to quickly start using some of the stacking software mentioned in this article.

What is the purpose of stacking photos The result is a single image with improved signal to noise ratio, i.e., with better details and lower (random) digital noise and better details.

The scheme below illustrates the concept.

If the considered digital noise affects the pixel values randomly across the stack, then the result of averaging the stack is that the random component of the noise to the pixel value is significantly reduced.

ISO noise and Luminance noise and Chrominance noise are examples of digital noises that are random.

The image below shows a real-life example from stacking 30 images from my Sony RX10 bridge camera taken at ISO 6400.

As you can see, the original images showed a greater deal of noise (grain) than the stacked one.

Comparison between the single image (top) (Sony RX10 ISO 6400) and the result of stacking 30 images (bottom).

The More Images You Stack, The Better The more images you stack, the cleaner the resulting images are, as shown in the comparison below.

The image shows the progression of quality improvement with the number of images stacked.

Sony RX10 ISO6400.

While Image stacking creates a cleaner image, it often softens the image: digital sharpening techniques are then used to recover sharp looking details.

Comparison between stacked image (top) and its sharpened version (bottom).

Finally, bear in mind that the progression of image quality is not linear.

Image Stacking And Movement If nothing moves between shots, like in the previous real life example, implementing image stacking is very simple: just group the images and average them to smooth out the noise.

With a moving subject, grouping and averaging the images will not only smooth out the noise, but also the subject itself.

This is the same principle for which long exposures of passing traffic and crowd result in a street image without cars nor people.

This is the resulting stack from 3 images where the astronaut was moved after each photograph.

You can still see the three faint positions where the astronaut was (indicated by the arrows).

This effect is amplified with the number of images used, and the moving subject could simply disappear from the stacked image.

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