this post was submitted on 29 Mar 2025
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[–] [email protected] 39 points 4 days ago (3 children)

Spectral JPEG XL utilizes a technique used with human-visible images, a math trick called a discrete cosine transform (DCT), to make these massive files smaller [...] it then applies a weighting step, dividing higher-frequency spectral coefficients by the overall brightness (the DC component), allowing less important data to be compressed more aggressively.

This all sounds like standard jpeg compression. Is it just jpeg with extra channels?

[–] [email protected] 31 points 4 days ago (1 children)

Yeah, it compresses better too though, and jpeg XL can be configured to compress lossless, which I imagine would also work here

[–] [email protected] 5 points 4 days ago (2 children)

Lossless JPEG would be amazing.

[–] [email protected] 5 points 3 days ago

JPEG 2000 supports lossless mode.

[–] [email protected] 3 points 4 days ago (1 children)

In my experience, as you increase the quality level of a jpeg, the compression level drops significantly, much more than with some other formats, notably PNG. I'd be curious to see comparisons with png and gif. I wouldn't be surprised if the new jpeg compresses better at some resolutions, but not all, or with only some kind of images.

[–] [email protected] 3 points 3 days ago

jpeg xl has been in development from FLIF for like 15 years there are tons of comparisons all over, even live ones on youtube

[–] [email protected] 5 points 3 days ago (1 children)

Kind of, but JPEG converts image data to its own internal 3 came channel colour space before applying DCT. It is not compressing the R, G and B channels of most images. So a multichannel compression is not just compressing each channel separately.

[–] [email protected] 1 points 3 days ago

Yeah, jpeg converts to lab (or something similar, I think). But the dimensions are the same: one channel for lightness, and then a number of channels one less than the total number of sampled frequencies to capture the rest of the color space.

[–] [email protected] 3 points 3 days ago* (last edited 3 days ago)

It's not just like jpeg with extra channels. It's technically far superior, supports loss less compression, and the way the decompression works would make thumbnails obsolete. It can even recompress already existing JPEGs even smaller without additional generation loss. It's hard to describe what a major step this format would be without getting very technical. A lot of operating systems and software already support it, but the Google chrome team is practically preventing widespread adoption because of company politics.

https://issues.chromium.org/issues/40168998

[–] [email protected] 21 points 3 days ago (2 children)

“And while Spectral JPEG XL dramatically reduces file sizes, its lossy approach may pose drawbacks for some scientific applications.”

This is the part that confuses me. First of all, many applications that need spectral data need it to be as accurate as possible. Lossy compression in that might not be acceptable.

More interestingly (and I’ll read the actual paper for this): which data will be more compressed? Simply put, JPEG achieves its best compression by keeping the brightness but discarding colour. Which dimension in which spectral space do the researchers think can be more compressed than others? In this case there is no human visual system to base the decision on.

[–] [email protected] 8 points 3 days ago

jpeg xl does support lossless and their 69 page paper does mention this so I am unsure why they are putting the lossy aspect of this as the comparison to their "lossless ZIP COMPRESSION of OpenEXR"

page 51 has more detail on compression stuff. The openEXR does also support lossy. Anyway I think page 51-52 would answer it for someone that knows more about openEXR which I sure don't

Their comparison images do clearly show data being lost as well so they aren't even using visually lossless of jpeg xl they are actually just going full lossy. Must be some use case somewhere?

[–] [email protected] 2 points 3 days ago

I literally can't think of a scientific use case where lossy compression would be acceptable?

[–] [email protected] 3 points 3 days ago

What, pickle.dump your enormous Numpy array not good enough for you anymore? Not even fancy zlib.compress(pickle.dumps(enormousNumpyArray)) will satisfy you? Are you a scientist or a spectral data photographer?