qoir

> Compressing QOI with something like LZ4 would generally outperform PNG. https://github.com/nigeltao/qoir has some numbers comparing QOIR (which is QOI-inspired-with-LZ4) vs PNG. QOIR has better decode speed and comparable compression ratio (depending on which PNG encoder you use). QOIR's numbers are also roughly similar to ZPNG.

Slides: https://filmroellchen.eu/talks/QOI%20EH25/#/0/1 As that data compression nerd, QOI is both a refresher and an annoyance. It serves as a good example that input modelling is very important, so much that QOI almost beats PNG in spite of very suboptimal coding. But QOI also represents a missed opportunity because, well, we can do much better if we are willing to use something like QOI instead of standard formats! Weirdly enough people seem to value only the simplicity when it comes to QOI, which is not the main takeaway I believe. Maybe QOIR [1] might result in a better balanced format in the future though... [1] https://github.com/nigeltao/qoir/

Not to mention the part where adding compressors like this somewhat defeats the purpose of using a simple format like QOI (although at least zstd is faster than gzip, let alone 7zip). But if we're modifying things like that, then they might as well make use of Nigel Tao's improved QOIR format, and replace the LZ4 compressor it uses with zstd. That's probably faster and likely compresses better than QOI. [0] https://nigeltao.github.io/blog/2022/qoir.html [1] https://github.com/nigeltao/qoir

It's important to notice that ZPNG beats virtually all QOI variants, as discovered in: https://github.com/nigeltao/qoir

I didn't infer 15% from the way it was written there. But most platforms these days have some form of CRC32 "acceleration". Adler32 is easy to compute so I'm even less concerned there. I spent a bunch of time optimising the code in fpnge (https://github.com/veluca93/fpnge), which is often notably faster than fpng (https://github.com/nigeltao/qoir/blob/5671f584dcf84ddb71e28d...), yet checksum time is basically negligible. Having said that, the double-checksum aspect of PNG does feel unnecessary.

All of these QOI derivatives improves upon the coding efficiency AFAIK. In QOIP, opcodes themselves are stored in the format, LZ4 or zstd compression https://github.com/chocolate42/qoipond QOIR adds: color profile, EXIF, premultiplied alpha, lossy mode, tile support, LZ4 compression, AFAIK it does this while beating the original QOI in terms of speed AND efficiency. Lots of benchmarks in: https://github.com/nigeltao/qoir QOIX is my very own version that adds: Greyscale [+alpha] 8-bit image support, lossy 10-bit support (16-bit encoded as 10-bit, intended for elevation maps), so it's really 3 codecs , optional LZ4. https://github.com/AuburnSounds/gamut

> Did you compile fjxl with or without SIMD? I had not. Thanks for the tip. Fjxl encoding speed is now about 20x faster than libpng, not 10x, but still mid-table. Decoding speed is unaffected. https://github.com/nigeltao/qoir/commit/c2fec840 > If existing deployments need to be replaced anyway, you can just as well use a new format altogether. There's still an operational difference between rolling out multi-threaded PNG versus multi-threaded $OTHER_FORMAT. At the file format level, MT PNG can be designed to be backwards compatible. Older PNG decoders simply ignore the new non-critical chunk. At the software level, you can roll out encoders that emit MT-capable PNGs without having to also roll out new decoders everywhere (or 99% everywhere, or 'on all major browsers'). You can roll out new decoders only partially, and those upgraded place

IIUC, the quality knob (not the effort knob) isn't relevant for lossless encoding. Knobs are also less relevant for lossless decoding, where there's only one correct output for any given input. In any case, my code (https://github.com/nigeltao/qoir/blob/main/adapter/jxl_adapt...) copy/pastes examples/encode_oneshot.cc from the libjxl repository, plus an additional JxlEncoderSetFrameLossless call. So I'm using whatever knob values that the libjxl example uses, i.e. the default knob values. If there are better knob values for lossless, let me know.

From the "Lossless Compression Performance" section of the article: > JPEG XL can do lossless image compression in a way that beats existing formats (in particular PNG) in all ways: it can be faster to encode, produces smaller files, and more... Does "in all ways" include any decode (not encode) speed numbers? Such numbers are dependent on the test suite, and I might be holding it wrong, but on my measurements, JPEG XL lossless encodes 10x slower and decodes 12x slower than PNG (the libpng implementation), and decodes 30x slower than PNG (the wuffs implementation). JPEG XL does admittedly win on compression ratio (smaller files), though. https://github.com/nigeltao/qoir/blob/main/doc/full_benchmar...