Before I roam other forums I though I ask here…

Anyone familiar with true Perlin Noise and the algorithmic/math behind it?

And I mean the true gradient noise, not the value noise with cubic interpolation poisoning the internet making kids think it’s Perlin

I am having troubles with 2 dimensional Perlin, the theory is all sound, but the first thing bugging me is, that the inner products of the gradient vectors in the lattice points create values n<-1 n>1.

What’s even worse, the scalar field of (x,x+1) does not match (x+1, x+2) at the seam… in either direction…

Maybe someone is interested in this, generally, mathematically or algorithmically…

btw, the implementation in 1d was no problem at all. Works flawlessly, even with fBm octaves on top of it.