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from the reduce-the-size-of-your-pron-storage dept.
With unlimited data plans becoming increasingly expensive, or subscribers being forced to ditch their unlimited data due to overuse, anything that can reduce the amount of data we download is welcome. This is especially true for media including images or video, and Google just delivered a major gain when it comes to viewing images online.
The clever scientists at Google Research have come up with a new technique for keeping image size to an absolute minimum without sacrificing quality. So good is this new technique that it promises to reduce the size of an image on disk by as much as 75 percent.
The new technique is called RAISR, which stands for "Rapid and Accurate Image Super-Resolution." Typically, reducing the size of an image means lowering its quality or resolution. RAISR works by taking a low-resolution image and upsampling it, which basically means enhancing the detail using filtering. Anyone who's ever tried to do this manually knows that the end result looks a little blurred. RAISR avoids that thanks to machine learning.
[...] RAISR has been trained using low and high quality versions of images. Machine learning allows the system to figure out the best filters to recreate the high quality image using only the low quality version. What you end up with after lots of training is a system that can do the same high quality upsampling on most images without needing the high quality version for reference.
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(Score: 2) by gidds on Friday January 20 2017, @01:26PM
Exactly.
And the real shame is that this sort of technology could be used in a real compression algorithm.
AIUI, many compression algorithms are based around a predictor: code that can make the best guess possible as to what the next byte/word/unit will be, based on the ones it's had already. Then, you encode the 'residual', the difference between the prediction and the actual value. The better the predictor, the smaller the residuals — and the better they can be compressed using existing techniques. (You can also apply lossy techniques to them, of course.)
So if this sort of AI makes better guesses about the detail of the image, then it can be used to improve image compression without making up detail out of whole cloth just because it's the sort of thing that other images have.
(Of course, if an ignorant amateur like me can come up with this idea, then I'm sure the experts have. Though none of the reports I've read about this story suggest so.)
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