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A virtual landscape generated using Perlin noise. Perlin noise is a procedural texture primitive, a type of gradient noise used by visual effects artists to increase the appearance of realism in computer graphics. The function has a pseudo-random appearance, yet all of its visual details are the same size. This property allows it to be readily ...
An artifact of some implementations of this noise is that the returned value at the lattice points is 0. Unlike the value noise, gradient noise has more energy in the high frequencies. The first known implementation of a gradient noise function was Perlin noise , credited to Ken Perlin , who published the description of it in 1985.
Perlin noise is the earliest form of lattice noise, which has become very popular in computer graphics. Perlin Noise is not suited for simulation because it is not divergence-free. Noises based on lattices, such as simulation noise and Perlin noise, are often calculated at different frequencies and summed together to form band-limited fractal ...
Noise in computer graphics refers to various pseudo-random functions used to create textures, including: Gradient noise, created by interpolation of a lattice of pseudorandom gradients Perlin noise, a type of gradient noise developed in 1983; Simplex noise, a method for constructing an n-dimensional noise function comparable to Perlin noise
The noise function then returns the interpolated number based on the values of the surrounding lattice points. For many applications, multiple octaves of this noise can be generated and then summed together, just as can be done with Perlin noise and Simplex noise, in order to create a form of fractal noise.
Abstract composition in 3D generated with the OpenSimplex noise generation algorithm. OpenSimplex noise is an n-dimensional (up to 4D) gradient noise function that was developed in order to overcome the patent-related issues surrounding simplex noise, while likewise avoiding the visually-significant directional artifacts characteristic of Perlin noise.
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You are right that people often confuse the noise primitive (be it Perlin or some other gradient or even value noise) with the FBM (fractal brownian motion) construction and derivatives, and that several layers or octaves (of smaller scales) are needed to create a more rich spectrum (usually of the form 1/f or 1/f^2).