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 New Google machine learning method reduces your mobile data traffic by enhancing low-res images

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PostSubject: New Google machine learning method reduces your mobile data traffic by enhancing low-res images   New Google machine learning method reduces your mobile data traffic by enhancing low-res images Empty2017-01-13, 15:15

Modern cameras are getting better and better. Contemporary DSLR devices and smartphone cameras alike are capable of capturing ultra-high res pictures, which allow us to see our World in the most detailed of ways.

However, a larger resolution usually leads to a bigger image size, and this fact does increase our overall data usage and the time it takes for a picture to load. You may say that this classifies as a First World problem, but it is a valid concern for many people that live in areas where data plans are pricey, or the internet is spotty.

Fortunately, Google appears to have invented a new technology that may be the salvation to our bandwidth troubles. Called RAISR (short for Rapid and Accurate Image Super Resolution), this new technique uses machine learning to produce high-quality versions of low-resolution images. RAISR differs from traditional upscaling approaches, as upscaling usually only adds more pixels to a low-res image, which might produce a less pixelated version of it, but does little in terms of bringing out more vivid and sharp details.

Example of an upscaled image

Example of an upscaled image

With this new method, Google takes a completely different approach, as it uses machine learning to train RAISR with pairs of images that consist of a low and high quality version of the same image. The software then finds filters that are selectively applied to each pixel of the low-res version, which produce a level of detail that is comparable to the original.

Google has implemented RAISR in its Google+ app for some Android handsets, and the results have been quite impressive. Essentially, the new method can reduce data usage per image viewed by up to 75%, as RAISR requests a version of the original picture that only has a quarter of the pixels, and then enhances and enlarges it to produce the same quality. On average, this slashes overall bandwidth usage by about a third.

Although this approach is currently in use only with Google+, Google product manager John Nack said that his team is planning to "roll this technology out more broadly". RAISR is already being applied to Google's photo library and is transforming 1 billion images per week, so it could possibly be employed to trim data usage for search results, Play Store graphics, YouTube thumbnails and other Google services.
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