Google's New Compression Tool Uses 75% Less Bandwidth Without Sacrificing Image Quality (thenextweb.com)
An anonymous reader quotes a report from The Next Web: Google just released an image compression technology called RAISR (Rapid and Accurate Super Image Resolution) designed to save your precious data without sacrificing photo quality. Claiming to use up to 75 percent less bandwidth, RAISR analyzes both low and high-quality versions of the same image. Once analyzed, it learns what makes the larger version superior and simulates the differences on the smaller version. In essence, it's using machine learning to create an Instagram-like filter to trick your eye into believing the lower-quality image is on par with its full-sized variant. Unfortunately for the majority of smartphone users, the tech only works on Google+ where Google claims to be upscaling over a billion images a week. If you don't want to use Google+, you'll just have to wait a little longer. Google plans to expand RAISR to more apps over the coming months. Hopefully that means Google Photos.
....is a lie, it reduces image quality just in a way you cannot see visually
If all you want to do is look at the image this is fine, but anything else that needs it full quality will be sacrificed
Puteulanus fenestra mortis
How well does it do if you replace the lower quality picture with a doodle? Of course this will be no good to the internet unless they open source it.
Build a Man a Fire, and He'll Be Warm for a Day. Set a Man on Fire, and He'll Be Warm for the Rest of His Life.
I didn't sign up for Google+ when they tried to force me to, and having won that battle, I'm sure as not going to now. I'll go to my eternal rest having never used Google+.
I don't give a fuck about anything server based like google photos. /usr/bin/raisr or it's just another something to enslave users, chain and binding them to an overlord.
I want
Do no evil my ass!
I can't wait until you get technology like this combined with eye tracking to decide on-the-fly what parts of your VR experience are the most visually important and can optimize rendering accordingly.
On of my main pet peeves with current VR is that I can't see why you'd need to render at full resolution outside of the eye's focus area, which should make it possible to massively reduce the rendering required to get amazing quality.
If you can also optimize by using machine learning to decide which areas are perceptually important that should make it possible to focus your processing resources even better on the parts that matter for the visual experience.
I'm a dreamer, the world is my playpen. But hey, I'm a serious person, I can't dream all the time.
52 Billion images a year? Damn, that's way more traffic than I ever would have expected on G+
Is it just my observation, or are there way too many stupid people in the world?
... something they stole from Pied Piper.
- Chuq
Summary's links are fact-free ads.
I found this one, that has the merit to link to the arXiv article about the process.
I have discovered a truly marvelous proof of killer sig, which this margin is too narrow to contain.
Given the number of pictures harvested by Google over the years, and provided that many people send the same boring pics (Eiffel t., China w., s. of Liberty...), in gmail for instance Google has just to put the index of the same stock picture they already have (say 8 bytes) and that's it. For a 8 MB pic, that's a 99.9999% compression rate.
Slashdot, fix the reply notifications... You won't get away with it...
Original Image size = X
Google says compressed Image = 0.25 X , but no loss of quality
So, apply algo on compressed image, and its 0.0625X
Now, assume original image is actually a representation of 1TB data as an image (barcode or whatever). Then after 2 rounds of compression it would be just 62 GB. Imagine the amount of bandwidth that can be saved, even better at 3-4 passes.
Make all connections 1Mbps, and pass all data through this algo 10 times at the source server. Suddenly there will be no bandwidth issues anywhere. Even conservatively, 1Mbps = 1 Gbps
RAISR (Rapid and Accurate Super Image Resolution) does not work... try Rapid and Accurate Image Super Resolution
The approach look quite interesting. It appears to be compressing by identifying parts of images that correlate with a data set generated using machine learning. From an information theory point of view this could work quite well for Google. Why store a million high resolution pictures of Justin Bieber, when you can just store enough to know it is Bieber, and then generate the detail you need from your Bieber database.
The potential space savings would be huge. Also, presumably the characterization system also leads towards the potential for a fast searchable mass image database.
Hooli actually beat Pied Piper in compression?!
"Rapid and Accurate Super Image Resolution" should give RASIR.
Which illiterate philistine came up with "RAISR"?
Shit, first it was vp8/WEBM but momentum seems to have died on that but now there's vp9 and it's better than vp8 and now images. Google you're annoying as fuck with the moving targets on your open standards, and while I think it's great that we now have another way to store images but we still have GIF, PNG, SVG, JPEG and even your own )(*@)(*! WEBP which is based on VP8 which you don't like anymore. So now with RAISR what do we all do start buying dart boards to figure out what standards we as ISVs should be targeting? None of the other formats are going away anytime soon but since vp8, vp8, WEBP and RAISR are all under your roof, can we ask that you make up your damn minds, please?!?!
Harrison's Postulate - "For every action there is an equal and opposite criticism"
Let's hope Google has had the forethought to have the image recognition algorithm pre-screen for images containing numbers, letters, and diagrams. Pattern-matching compression can be pretty scary when it decides two patterns are close enough:
http://www.dkriesel.com/en/blo...
The algorithm is not for compression, but for enhancing a low resolution version of the image.
So two files have to be in storage and loaded into memory to which use electrons. Then a third image must be created which uses electrons. Finally the image must be transmitted. Ok, that transmission uses less electrons than the the transmitting the larger scale image, but you probably haven't saved any energy by doing the transform, and likely have burned more fossil fuels in the process.
Remember when PNG was supposed to be the format that would finally "end the tyranny of JPEG"?
Anyone remember FlashPix?
Anyone?
Bueller?
This is like the language du jour that comes up once or twice a year that will "end the tyranny of C++".
WEBM is video, and the momentum didn't die, when you view a "gif" on imgur you're actually viewing a webm, they just decided to use the wrong extension name. WEBM uses the VP9 codec. WEBP on the other hand is just a container format for the VP8 codec, which was derived from how frames were stored in WEBM when it was VP8-based. WEBP could upgrade to VP9 without changing the format, however it would require developers to link against a new library. And, the changes to VP9 were mostly advancements in moving video so they decided not to bother with static images. RAISR isn't a format, from what I understand, it's an algorithm that requires an entire cloud-based platform running a machine learning heuristic designed to scale images in a way that doesn't look quality but saves on bandwidth. My guess is that it could be applied to any image format eventually. Not only are these technologies open source, and in some ways technically superior to competitors, but they're uninhibited by patents. The world owes Google a big favor for the work they've done.
Will it still look good on Desktop monitors or is this only durable for showing the images on a mobile device? Personally I prefer to look at pictures on a larger display and low quality compressing is easy to spot in those cases
Rapid and Accurate Super Image Resolution
Sounds like the name of a Japanese game show.
It must have been something you assimilated. . . .
What's the Weissman score?!
Duplicate of Is Google's AI-Driven Image-Resizing Algorithm Dishonest? (November 19, 2016)
"No man's life, liberty, or property are safe while the legislature is in session." -- Judge Gideon J. Tucker
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