Recently a group of us went up on the roof and looked through it. It was a cloudy night, but we were able to look at the Moon and Jupiter. Looking at Jupiter we could see weather bands and the four Galilean satellites. The Moon was really very bright, so I tried pointing my little digicam through the eyepiece. It did a reasonably credible job, enough that I can show what the seeing is like:
At an amateur level, though, there is a trick that can help deal with bad seeing. It's called "lucky imaging", and looking at the video, it should be pretty clear how it can work: just take a video, throw out all the frames that are blurry, line up the ones that are left, and add them together to beat down the noise. Again you need a bright star (or something) in the frame to do the selection and alignment.
In this particular case, the Moon is so bright I don't need to stack multiple images, so I just ran a Laplacian filter over each frame and selected the one with the highest RMS value. Which is how I got the image at the top of the page.
3 comments:
It's a pity the seeing causes such localized distortion, otherwise it might have been easier to apply registration + super-resolution.
Are there any characteristics of the seeing that could be used to remove it with, e.g., deconvolution?
There are tricks like that that can be done in the image analysis domain. But it's a challenge to even take images this quickly without getting swamped by per-image noise - even with a big telescope you get photons trickling in. And with a big telescope you tend to be averaging over many cells, so all-good images are even rarer.
The best approach to dealing with this is called "adaptive optics", where you use "wavefront sensors" to map the optical distortion produced by the atmosphere, and deformable mirrors to reverse it. This is apparently a real pain to keep working, but when it does it can really clear up the image. It turns out that if you can combine this with lucky imaging, you can do even better.
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