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Researchers Devise AI System To Reduce Noise in Photos (venturebeat.com)
Researchers from Nvidia, MIT, and Aalto University are using artificial intelligence to reduce noise in photos. The team used 50,000 images from the ImageNet dataset to train its AI system for reconstructing photos, and the system is able to remove noise from an image even though it has never seen the image without noise. VentureBeat: Named Noise2Noise, the AI system was created using deep learning and draws its intelligence from 50,000 images from the ImageNet database. Each came as a clean, high-quality image without noise but was manipulated to add randomized noise. Computer-generated images and MRI scans were also used to train Noise2Noise. Denoising or noise reduction methods have been around for a long time now, but methods that utilize deep learning are a more recent phenomenon.
I have a couple of thousand images that would benefit from noise reduction. Shooting movement in low light means high ISO or blur, so I accept the noise.
If they wanted some serious training data, the whole astrophotography field is full of people that take dozens of pictures of the same thing then sample across all of them to remove noise. That means they have plenty of randomness in their noisy images and a nice clean one for comparison.
It would be interesting to see a visual diff between the denoised result and the source image before the random noise was added, in order to see what kinds of artifacts were generated during the denoising process. For example, did it add any leaves to the image of the koala?
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