The images are actually not that degraded. There's a large amount of colour noise when amplified, but there's plenty of detail. Photographers can pull stuff out

The images are actually not that degraded. There's a large amount of colour noise when amplified, but there's plenty of detail. Photographers can pull stuff out of shadows all the time, but properly fixing noise is a pain in the backside. For example: http://web.engr.illinois.edu/~cchen156/SID/examples/book.html http://web.engr.illinois.edu/~cchen156/SID/examples/book.htm... What this net seems to be much better at is identifying which parts of the image are a result of noise and what the true intensity is. I'd love to see this used in astrophotography. Remember that RAW data is generally more than 8-bits of dynamic range and image sensors are quite sensitive. You might not be able to tell the difference between 0-5 counts on an 8-bit image, but at 12-bit that's 60 counts difference. I did some work during my PhD on laser spot detection in images (12-bit mono in my case). Even when I set the camera exposure down to several thousandths of a second, in a dark room, you could almost always recover some/all of the structure (tables, other objects, calibration patterns, etc). EDIT: If I were a reviewer on this paper I would ask for histograms of the input/output images, or at the very least something like mean counts in the image. 1/30s at 0.1 lux - great, do you know how many counts that is on the arbitrary sensor that was used? I sure don't. You could check this in the supplementary data, but it's an annoying omission in the paper.