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  2. Perlin noise - Wikipedia

    en.wikipedia.org/wiki/Perlin_noise

    Perlin noise is a type of gradient noise developed by Ken Perlin in 1983. It has many uses, including but not limited to: procedurally generating terrain , applying pseudo-random changes to a variable, and assisting in the creation of image textures .

  3. Simulation noise - Wikipedia

    en.wikipedia.org/wiki/Simulation_noise

    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 ...

  4. Gradient noise - Wikipedia

    en.wikipedia.org/wiki/Gradient_noise

    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.

  5. Procedural generation - Wikipedia

    en.wikipedia.org/wiki/Procedural_generation

    Coherent noise can be extremely important to procedural workflow in film. Simplex noise is often faster with fewer artifacts, though an older function called Perlin noise may be used as well. Coherent noise, in this case, refers to a function that generates smooth pseudo-randomness in n dimensions.

  6. OpenSimplex noise - Wikipedia

    en.wikipedia.org/wiki/OpenSimplex_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.

  7. Simplex noise - Wikipedia

    en.wikipedia.org/wiki/Simplex_noise

    Simplex noise. Simplex noise is the result of an n-dimensional noise function comparable to Perlin noise ("classic" noise) but with fewer directional artifacts, in higher dimensions, and a lower computational overhead. Ken Perlin designed the algorithm in 2001 [1] to address the limitations of his classic noise function, especially in higher ...

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  9. Worley noise - Wikipedia

    en.wikipedia.org/wiki/Worley_noise

    Worley noise, also called Voronoi noise and cellular noise, is a noise function introduced by Steven Worley in 1996. Worley noise is an extension of the Voronoi diagram that outputs a real value at a given coordinate that corresponds to the Distance of the nth nearest seed (usually n=1) and the seeds are distributed evenly through the region.

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