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jpeg 2000 had about a 20% reduction in size over typical jpeg, while producing virtually no blocking artifacts, 16 years ago[1]. Almost no one uses it, though.
by richard_todd 10y ago
jpeg 2000 had about a 20% reduction in size over typical jpeg, while producing virtually no blocking artifacts, 16 years ago[1]. Almost no one uses it, though. Now in 2016 we are using neural networks to get a similar reduction, except the dog's snout looks blurry, and with a process that I assume is much more resource intensive. It's interesting for sure, but if people didn't care about jp2, they would have to be drinking some serious AI Kool-aid to want something like this.
[1]: https://en.m.wikipedia.org/wiki/JPEG_2000 https://en.m.wikipedia.org/wiki/JPEG_2000
- aub3bhat 10y agoRather than using misguided phrases like "Kool-aid" its important to consider several reasons why JPEG 2000 adoption has lagged or why there is interest in neural networks: 1. JPEG 2000 is Patent encumbered. 2. Neural Network methods have good chance of getting significantly better. 3. The way similar architecture / ops have been found to be very effective across variety of tasks, its not unlikely that in future, all machines will have a dedicated neural inference chip, e.g. NVidia Jetson TK1 or Google TPU. In this scenario the more mileage you can get out of such dedicated hardware the better.
- lawpoop 10y ago1 seems valid, but 2 and 3 don't seem to be a reason applicable going back the past 16 years. That would be a kind of vaporware argument if we would have had to have waited 16, 10, or even 5 years for NN improvements over JPEG 2000 to pan out.
- visarga 10y ago> Now in 2016 we are using neural networks to get a similar reduction It's a proof of concept, not to be used in real life for anything. It would be too expensive. Also, it's not a refined product, just an attempt to see if neural networks can do better compression.
- richard_todd 10y agoYeah that's not lost on me. I'm just trying to put the accomplishment in context. To me, (misguided as I may be LOL), it means the state of the art for NN photo compression is getting close to what we could do with wavelets in the late 90's. I don't mean to say that's bad; in fact I think that's pretty amazing. It's also good to maintain some perspective on what it's actually worth to do better than JPEG. We have had actual usable products better than JPEG for a long time (I mentioned J2K but there's been so many others like WebP and BPG etc), and no one cares. People use GIF as a short-form video format--that's how much no one cares about this stuff. So I think it's mostly worthwhile as research, to increase our ability with neural nets in general, rather than as an eventual product. But who knows?
- ekianjo 10y agoAnd since 2016 we have FLIF too.
- franzb 10y agoNote that DCP, the Digital Cinema Package standard for distributing films in digital forms, uses JPEG 2000 to compress each frame: https://en.wikipedia.org/wiki/Digital_Cinema_Package https://en.wikipedia.org/wiki/Digital_Cinema_Package
- svantana 10y agoThere's also BPG [1], a javascript image decoder that can be used on the web today, with (in my estimate) about a 40% improvement over jpeg. It's a bit disingenuous to use something so far from the state of the art as baseline, but it's still an interesting line of research IMO. [1] http://bellard.org/bpg/ http://bellard.org/bpg/
- wyoh 10y agoBPG is derived from HEVC and thus patent encumbered as JPEG2000. But we have new codec like Daala or AV1 that could be used as a still image formats when they'll be mature enough. I made a website where one could compare various formats: http://wyohknott.github.io/image-formats-comparison http://wyohknott.github.io/image-formats-comparison
- tudorsuciu 10y agoYou can use Bpg in Linux with: https://github.com/tudorsuciu/bpg-pixbuf-loader https://github.com/tudorsuciu/bpg-pixbuf-loader