You can find plenty of information out there on various standard image and signal processing algorithms. Basic stuff like 2D convolutions form the backbone of many image processing techniques, and they’re well documented.
But just like Reed-Solomon encoding is a very specific algorithm, with many different applications, of which QR codes is one. What you’re looking for is similar, it’s a huge set of very specific algorithms with huge set of applications, of which one is QR codes.
QR codes are simply too niche for anyone to have put together a pubic document on what exact image processing techniques you might use to decode them. If you want to teach people about 2D signal processing, then QR codes are probably not a good starting point.
I would also argue that Reed-Solomon encoding is not “deep” anything. It’s one of many different 1D signal error correction algorithms that exist. For people who work on signal processing as day job, Reed-Solomon is about as “deep” as quick-sort is to programmers.
As for why quick-sort is well documented with many open implementations, and QR codes aren’t. I would argue it’s simple due to the industry they developed in. QR codes started in manufacturing, being used for inventory management, almost certainly by embedded and electronic engineers. All of those industries pre-date the open source movement by decades, trade secrets are still important for them, so they’re not naturally inclined to share IP.
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You can find plenty of information out there on various standard image and signal processing algorithms. Basic stuff like 2D convolutions form the backbone of many image processing techniques, and they’re well documented.
But just like Reed-Solomon encoding is a very specific algorithm, with many different applications, of which QR codes is one. What you’re looking for is similar, it’s a huge set of very specific algorithms with huge set of applications, of which one is QR codes.
QR codes are simply too niche for anyone to have put together a pubic document on what exact image processing techniques you might use to decode them. If you want to teach people about 2D signal processing, then QR codes are probably not a good starting point.
I would also argue that Reed-Solomon encoding is not “deep” anything. It’s one of many different 1D signal error correction algorithms that exist. For people who work on signal processing as day job, Reed-Solomon is about as “deep” as quick-sort is to programmers.
As for why quick-sort is well documented with many open implementations, and QR codes aren’t. I would argue it’s simple due to the industry they developed in. QR codes started in manufacturing, being used for inventory management, almost certainly by embedded and electronic engineers. All of those industries pre-date the open source movement by decades, trade secrets are still important for them, so they’re not naturally inclined to share IP.