But that doesn’t mean the process of compression involves significant amounts of unpredictable branching operations. If for no other reason than it would be extremely slow and inefficient, because many branching operations means you’re either processing input pixel-by-pixel, or your SIMD pipeline is full of dead zones that you can’t actually re-schedule, because it would desync your processing waves.
Video compression is mostly very clever signal processing built on top of primitives like convolutions. You’re taking large blocks of data, and performing uniform mathematical operations over all the data to perform what is effectively statistical analysis of that data. That analysis can then be used to drive a predictor, then you “just” need to XOR the predictor output with the actual data, and record the result (using some kind of variable length encoding scheme that lets you remove most of the unneeded bytes).
But just like computing the median of a large dataset can be done with no branches, regardless of how random or the large the input is. Video compression can also largely be done the same way, and indeed has to be done that way to be performant. There’s no other way to cram up to 4k * 3bytes per frame (~11MB) through a commercial CPU to perform compression at a reasonable speed. You must build your compressor on top of SIMD primitives, which inherently makes branching extremely expensive (many orders of magnitude more expensive than branching SISD operations).
