Like, it's baffling to me how much we can compress high-quality video nowadays. HEVC and AV1 and VP9 are all also very cool and they still sort of break my brain. I understand how they work but it doesn't feel like it should compress as well as it does.
The context heavily implies that quantization is "discarding information" generally (e.g. clipping, masking). The wikipedia article he links in the footnote disagrees, and so do I:
> quantization is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often with a finite number of elements.
Quantization is a function over values, or the image itself. Clipping and masking, by contrast, are functions over the space/frequency dimensions, i.e. the pixel indices ("preimage"). A rule like "apply a circular mask" or "drop the first quadrant" does not depend on the values!
The most extreme example of quantization is a threshold filter. Regardless of location, output "1" if the pixel is brighter than X, or "0" otherwise. This depends only on the value, not on the location. He also misses the opportunity to point out that chroma subsampling is another application of quantization, this time to chroma values (drop the low-order bits).
Codecs like H.264 and JPEG use spatially-varying quantization rules to effectively discard more information at high frequencies, so his explanation of H.264 is spot on, but a non-expert encountering quantization for the first time would probably come away with the wrong idea. For an article explicitly targeted to non-experts that goes out of its way to introduce the term, it's a pretty important oversight.
To build on the example used in the article, you could quantize an image by dropping the lower half of the bits of every pixel value. This discards half the information by mapping the larger input image space (e.g. 8 bits per pixel) to a smaller output image space (e.g. 4 bits per pixel), effectively scaling/rounding the original values.
The fact that higher frequencies can be quantized more intensely with relatively little image quality loss is a completely separate idea from quantization itself. In this context, high frequency masking as described in the article could be accurately described as a spatially dependent quantization to zero-bit output values. But the quantization part is the mapping, not the shape of the mask, and I think the article is misleading about the distinction.
In real codecs, there usually isn’t a hard boundary like a mask, but instead an empirical table of how many bits to keep based on the perceptual value of the information at each frequency.