What I like about this approach is that it requires zero differential calculus. People forgot that Radix2 DCTs come from a century's worth of advanced math in the S domain. This approach is applied-computer-science based, I can get my head around that a lot better than a Laplace/Z transform.
But what shocks me is how did absolutely no-one apply such a naive RLE in the 30 years of internet image formats?
Is this a case of "man reinvents wheel again because why do research" or is this exceptional?
RLE on runs of deltas is in very many compression schemes; it's a common technique (probably so common that many authors don't deem it worth mentioning). Lossless video codecs in particular (huffyuv, lagarith, utcodec, etc.) have had this going back 20 years at least.
we applied rle encoding for time-series and triac control systems 43 years ago after getting some guidance from a mainframe guy - but since RLE is practical so that we even use it to give direction to people on the street, its probably so old that its even found its way into the way our genes are encoded. :D
Just to add to this list, even MacPaint used RLE on a per-scan line basis. I recently wrote about decoding MacPaint files[0]. So, replying to the gp post, yes it is in a sense reinventing the wheel. But sometimes the wheel needs to get reinvented because you have a new vehicle that could use a different type. And I would say the original poster felt he needed part of the modern wheel without the tire, so he had to go back to earlier wheel designs in a modern context. Okay, I've stretched the analogy too far!
But what shocks me is how did absolutely no-one apply such a naive RLE in the 30 years of internet image formats?
Is this a case of "man reinvents wheel again because why do research" or is this exceptional?