My understanding is that it has gotten fairly complex. Don't know if they still use this particular facet but look at the Fourier-Mellin transform: <https://sthoduka.github.io/imreg_fmt/docs/fourier-mellin-tra...>

They don't use the highest frequencies as those watermarks are easy to obliterate, and they don't use the lowest frequencies as those would noticeably affect quality, the focus is generally on the mid range frequencies. However for A/B watermarking in particular which involve 1-bit watermarks, low frequencies may actually be fair game.

Keep in mind that when embedding watermarks of significant size (>100 bits) as for example if you want to create a camera that includes the serial of the device in every photo, error correcting codes would also be used. For 1-bit watermarks the error correction is likely ad-hoc and involves constructing some mathematical object (for example, a few real numbers derived from frames of a segment) which remains approximately fixed through transformations, you can afford to be wasteful.

It depends on which vendor they're using.

It generally occurs as patterns which are slightly in the noise. Good systems pick locations where its easier to hide and turn it off when the scene would expose it. Usually when badly done increasing sharpness in a scene can help reveal it.

Basically, if you can damage the watermark the picture quality is bad enough that it's harming your viewing. You need to compress into crap SD quality to make it hard to detect and even then you'll get something.

You don't even need a complete pattern, if you can get enough fragments you can narrow down the possible identities until you have a high match probability. I.e. partial fingerprints or DNA match.