While we’re big fans of Earth’s atmosphere for keeping us alive, it does hamper our ability to take crystal-clear images of deep space.
That’s why Emma Alexander of Northwestern University in Illinois and Tianao Li of Tsinghua University in Beijing have developed new AI-powered software that can sharpen such images.
Earth’s atmosphere often blurs images taken by ground-based telescopes. “It’s a bit like looking up from the bottom of a swimming pool,” Alexander said in a statement. “The water pushes the light around and distorts it. The atmosphere is, of course, much less dense, but it’s a similar concept.”
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This poses a problem for scientists studying images of deep-space objects.
“Slight differences in shape can tell us about gravity in the universe. These differences are already difficult to detect,” said Alexander. “If you look at an image from a ground-based telescope, a shape might be warped. It’s hard to know if that’s because of a gravitational effect or the atmosphere.”
While removing atmosphere-induced blur is a standard part of astronomical image processing, this new AI-powered tool is more accurate than classic methods and more modern methods of blur removal — by 38.6% and 7.4%, respectively.
The new technique is an adaptation of existing software used to sharpen photographs, but this marks the first time it’s been applied to images from ground-based telescopes.
To train the deep-learning AI, the team used images taken by the Hubble Space Telescope — which doesn’t have atmospheric blur due to its location in Earth orbit — introduced simulated atmosphere-induced blur, and downsampled the images to the resolution of the Vera C. Rubin Observatory, a powerful telescope currently under construction in Chile. Once Vera Rubin comes online in 2024 or so, the software will be perfectly calibrated for immediate use.
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Alexander and Li have made the software code open-source, which allows anyone to adapt it to different observatories. “Now we pass off this tool, putting it into the hands of astronomers,” said Alexander. “We think this could be a valuable resource for sky surveys to obtain the most realistic data possible.”
A study about the software was published in the journal Monthly Notices of the Royal Astronomical Society on March 30.
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