Taking a photo in poor lighting can often result in something too pixelated and noisy to be useful. Advanced software processing on some phones and cameras can fix moderate noise, but a new project from Nvidia, MIT, and Aalto University uses AI to correct for extreme levels of noise. Even if the “Noise2Noise” system has never seen an image before, it can de-noise it to get something very close to the original.
Noise2Noise is a neural network, which means you need to train it with lots of data. The team used 50,000 images from the ImageNet database, which contains clear, high-resolution images. Of course, the network needs to see noisy images in order to understand how to de-noise them. So, the team artificially added noise to the images and used those to train the algorithm.
Nvidia contributed a bank of Tesla P100 GPUs to run the network training with the cuDNN-accelerated TensorFlow deep learning framework. The network was adjusted until it was able to take out the noise and deliver something close to the original dataset image. The true test is how the network handles new images that it hasn’t seen before. The team reports that Noise2Noise can remove artifacts and noise with a high degree of accuracy.
Researchers point to several possible applications for Noise2Noise. Low-light photography is probably the one that would make the biggest immediate impact on your life. You could run your noisy photos through Noise2Noise and end up with something that looks much nicer. Astrophotography often involves very long exposures, and that leads to high noise. The same process could be applied here to make images of space clearer. MRI images suffer from similar noise issues, and the team tested Noise2Noise as a way to clean them up.
Many camera and smartphone manufacturers have their own processing algorithms that strip noise out of RAW images before showing you the final jpeg. For the most part, they don’t rely on the same technology as Noise2Noise. The only one that’s close is Google, which has leveraged its machine learning technology in the Pixel camera to do similar noise reduction work. However, it’s nowhere near as extreme. Noise2Noise can resolve detail from an almost unrecognizably pixelated image. The final product does look a bit unnaturally smooth, but that’s an issue even with less powerful image processing.
The researchers are presenting their work at the International Conference on Machine Learning in Stockholm, Sweden. It’s still just a computer science curiosity at the moment, but image processing is big business. A practical application could be a big hit.
Intel Launches AMD Radeon-Powered CPUs
Intel's new Radeon+Kaby Lake hybrid CPUs are headed for store shelves. Here's how the SKUs break down and what you need to know.
Huawei’s Phone Deal With AT&T Reportedly Killed On Account of Politics
The upcoming (and unannounced) deal with AT&T to sell the new Mate 10 series was supposed to be the start of Huawei's push into North America, but the deal has reportedly fallen apart at the last minute after AT&T got cold feet, and some sources point to a political cause.
IBM Plans to Reassign 31,000 Workers, Will Cut 10,000 Positions in 2018
IBM is firing over 10,000 workers and reassigning 30,000 more as part of yet another round of downsizing and reassignment.
NASA Finds Vast Deposits of Ice Just Under Martian Surface
We've known for years that there is at least some water ice on Mars, but it's been hard to pin down where it is and how easy it would be to extract. New data from NASA's Mars Reconnaissance Orbiter indicates it could be almost everywhere.