Parametric Press is a magazine of interactive explorable explanations on topics like image compression, algorithmic bias, climate and housing data.
HN commenters praise its interactive essay on the JPEG format and its accessible primer on bias in machine learning systems.
Preface: It's difficult to write about stuff like this and I know reading it back to myself after will leave me wanting to redraft it 5 times over but it's 1am already. But, if this post is wrong/incorrect or is missing other factors that are too important to leave out then please let me know and I'll amend or even delete it. My focus is on the technical side of things. So anyway:
> why it itsn't the case for other image formats in which encodings color in RGB?
The term "RGB" doesn't mean anything w.r.t. gamut, gamma, dynamic-range, nor how necessarily non-linear transformations between color-spaces are performed. But all that's irrelevant: JPEG'S colour support is actually quite fine (...if you don't mind chroma subsampling), whereas the problem here relates to how JPEG decides what part of the image are important for high-quality preservation (more bits, more quality) than other areas (less bits, less quality).
Obligatory ADHD relevant-yet-irrelevant diversion: this excellent (fun and interactive!) article about how JPEG works: https://parametric.press/issue-01/unraveling-the-jpeg/
(Caution: incoming egregious oversimplification of JPEG):
Now, just imagine a RAW/DNG photo of the sky with some well-defined cumulus clouds in, and another RAW/DNG photo of equal pixel dimensions and bit-depth (so if they were *.bmp files they'd have identical size), except the second photo shows only a grey overcast sky (i.e. the sky is just one giant miserable old grey duvet that needs…
For JPEG compression: https://parametric.press/issue-01/unraveling-the-jpeg/#parametric-tooltip-2 (anchor doesn't work for me, but it's the one with the caption "Move slider to adjust the amount of subsampling applied." which made me understand the motivation behind using chroma)
For polygon sum/union/difference: https://sean.fun/a/polygon-clipping-pt1/ (the diagram captioned "Combined Fill Annotations" at https://sean.fun/a/polygon-clipping-pt2/#annotating-segments is my favourite visual proof)
For cryptanalysis: https://random.tastemaker.design
For Fourier transforms: https://brianmcfee.net/dstbook-site/content/ch05-fourier/Similarity.html
For digital typesetting of Arabic: https://lr0.org/blog/p/arabic/
Check out Unraveling the JPEG from Omar Shehata on Parametric Press[1] for an interactive essay on the JPEG format.
Very cool to be able to manipulate the bytes directly and seeing how it affects the image.
[1] https://parametric.press/issue-01/unraveling-the-jpeg/
I haven't used it, but there's idyll[0], which was used, among other things, to make an excellent interactive article about the JPEG format[1].
[0] https://idyll-lang.org/
[1] https://parametric.press/issue-01/unraveling-the-jpeg/
Not specific to facial recognition but covers it and the deeper issues. It is a thorough yet accessible primer on the many ways bias can creep into these systems:
https://parametric.press/issue-01/the-myth-of-the-impartial-machine/