Mastering Astrophotography: Overcoming Newton's Rings for Clearer Images

Greetings, astronomy enthusiasts! Have you encountered pesky circular patterns disrupting your solar images? These are Newton's rings, caused by light interacting with closely spaced surfaces like lenses and glass plates. They compromise the image and feel like a stutter-step in your brain, but fear not! We'll equip you with effective strategies to enhance your astrophotography by mitigating these rings. Let's dive in and restore the captivating beauty of your celestial images.

It should be noted that Newton's rings can be prevented before you start imaging by tilting your camera slightly (check out our favorite camera tilters below). But for existing rings, let's learn how to remove them!

To do this we are going to use a software called Affinity Photo 2. This is a paid program, though there is a free trial version. Aside from all the standard image-processing tools you'd expect, Affinity includes dedicated astrophotography tools like registration, calibration, stacking, background removal, and more. It can be customized with macros to speed up your processing workflow, and since a subscription isn't required, it's a compelling alternative to Photoshop.

Step 1: Open Your Picture

First things first, open up the picture that has those Newton's rings. It doesn't matter if it's colorful or black and white – these steps work for both.

Step 2: Deal with the Background

Sometimes you might see a bit of the sky's background in your picture. No problem! You can use the magic wand tool to select that sky part and get it ready for some fixing.

Step 3: Get Ready for the Magic

Now, before we start cleaning up the rings, here's a trick to make things easier. Make a copy of your picture's background by pressing Ctrl-C and then Ctrl-V. After that, press Ctrl-D to unselect anything you had selected before.

Step 4: Fix Those Rings

Look for a menu called Filters, then find Noise, and click on FFT Denoise. A window will pop up, showing your picture in a different way. Don't get confused! This is where the magic happens. For more detail about what's going on behind the scenes, read further!

Step 5: Zoom In and Get Rid of the Rings

Zoom in on the middle of the picture until you see individual dots clearly. Those rings we're talking about should look like two bright spots off-center.

Now, get your brush tool and make it small – about 2-3 pixels. Click on the edge of those bright spots, and keep clicking until they're all blacked out. Don't try to drag your brush – just do single clicks. The cool thing is, your edits will automatically happen on the other side too!

Step 6: Finish Up

After you're done with your clicks, close the pop-up window and wait for a moment. Your picture will change as the magic does its thing.

Step 7: Ta-Da!

And that's it! You've done it. The rings are gone, and your picture is looking awesome. You've turned a not-so-great photo into a fantastic cosmic masterpiece. Keep up the good work, and enjoy capturing the beauty of the universe without those interference rings getting in the way!



Video Walkthrough

How does it work?

The Fast Fourier Transform (FFT) is an algorithm used to decompose an image into sines and cosines of varying amplitudes and frequencies, which reveals patterns within the image. The FFT is widely used in various fields, including signal processing, audio processing, image processing, data analysis, and many more.

Any repeating pattern in an image will become immediately apparent in an FFT. Using a technique called FFT notch filtering we can remove specific frequencies or frequency ranges from a signal or an image in the frequency domain just by blacking out the specific ones we don’t want. In doing this, we will eliminate unwanted frequency components while preserving other parts of the signal or image. Newton's rings are the unwanted frequency component (pattern) in this case.

Applying a Fast Fourier Transform (FFT) notch filter to a digital image involves the following steps:

  • First, the digital image is converted from the spatial domain to the frequency domain using the 2D FFT.
    •  Brightness in the frequency domain image corresponds to amplitude in the sine or cosine components of the image - this means that patterns in the image are visualized by bright spots in the FFT. The brightest group are the low-frequency features we are looking to remove.

The FFT representation of the solar image containing Newton Rings. Bright features represent different patterns in the image. Our Newton rings show up as symmetrical v-shaped bright spots in the upper right and lower left quadrants.


  • In the frequency domain, a notch filter can be represented as a mask, which is a 2D array of the same size as the frequency domain image. The mask is initialized with all ones (indicating no suppression) and then set to zero in the region where the notch should be applied. We create these areas manually using Affinity's brush tool. In this case, we want to apply the mask to the bright spots that represent Newton’s rings. Affinity helps us visualize our edits to the mask as dark areas of the frequency domain image.
  • Apply the inverse FFT to the filtered frequency domain image to transform the image back to the spatial domain. This will give you the filtered image with the specified frequencies removed.

Affinity Photo does all of this in the background, allowing us to remove unwanted patterns in just a few clicks. It's almost like magic!

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