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On the contrary, batches of images with a high degree of similarity compress _very_ well. You have to use an algorithm specifically designed for that task thoug
by d110af5ccf 6y ago
On the contrary, batches of images with a high degree of similarity compress _very_ well. You have to use an algorithm specifically designed for that task though. Video codecs are a real world example of such - consider that H. 265 is really compressing a stream of (potentially) completely independent frames under the hood.
I'm not sure what the state of lossless algorithms might be for that though.
- cerved 5y agoright but we're not talking about compressing a video stream but compressing individually compressed pictures, big difference
- water8 6y agoA movie is a series of similar images and while it does allow temporal compression in a 3rd axis to the 2d raster, H265 is about as good as it gets at the moment but its also lossy which might not be tolerable.
- papageek 6y agoH266 VVC looks impressive. Waiting to get my hands on fpga codec for testing.
- simcop2387 6y agoBest I know of for that is something like lrzip still, but even then it's probably not state of the art. https://github.com/ckolivas/lrzip https://github.com/ckolivas/lrzip It'll also take a hell of a long time to do the compression and decompression. It'd probably be better to do some kind of chunking and deduplication instead of compression itself simply because I don't think you're ever going to have enough ram to store any kind of dictionary that would effectively handle so much data. You'd also not want to have to re-read and reconstruct that dictionary to get at some random image too.