Noise: 2d vs 3d, Perlin and Simplex


In yesterday’s post, I ran across this statement about Simplex noise:

noise generated for different dimensions are visually distinct (e.g. 2D noise has a different look than 2D slices of 3D noise, and it looks increasingly worse for higher dimensions).

As promised, here’s an analysis of what that actually means visually for rendering Simplex noise.

Curl Noise, Demystified


In my recent post on mapping Perlin noise to angles, I was put on to the subject of Curl noise, which I thought I understood, but did not. I figured out what Curl noise really was in a subsequent post and then posted my earlier incorrect (but still interesting and perhaps useful) concept of Curl noise in yet another post. Although I kind of understood what Curl noise was at that point, I wanted to give myself a more complete understanding, which I usually do by digging into the code, making sure I understand every line 100% and seeing what else I can do with it, trying to make multiple visualizations with it to test my understanding, etc.

Curl Noise


My last post on Perlin noise wound up on hitting Hacker News, which generated an enormous amount of views, and a fair number of comments – here, on Twitter, and on HN itself. Of course, there was the usual eye-rolling, condescending, “why doesn’t he just do ….? that would be the obvious approach” kind of comments there, but a fair amount of actual helpful ideas, explanations, and links. One thing that came up over and over was the idea of using curl noise. So, when I got a chance, I went ahead and used curl noise.