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  1. Perlin noise - Wikipedia

    Perlin noise is a type of gradient noise developed by Ken Perlin in 1982. It has many uses, including but not limited to: procedurally generating terrain, applying pseudo-random changes …

  2. Perlin noise: What is it, and how to use it. - blog.hirnschall.net

    Aug 27, 2020 · Perlin noise is a type of gradient noise that can be used to generate "smooth" randomness in one or more dimensions. This is why it is often used in the movie and special …

  3. Perlin noise (article) | Noise | Khan Academy

    Ken Perlin developed the noise function while working on the original Tron movie in the early 1980s; he used it to create procedural textures for computer-generated effects. In 1997, Perlin …

  4. The Ultimate Perlin Noise Guide - numberanalytics.com

    Jun 15, 2025 · Learn the ins and outs of Perlin Noise and take your visual effects to the next level with this in-depth guide.

  5. Learning how Perlin noise works - Huttar

    Caveat: Is that noise really Perlin? I've discovered in several places on the web, including in the writings of respected computer graphics experts, misleading references to "perlin noise" that …

  6. Perlin Noise - gameidea

    Nov 12, 2024 · Perlin noise is a type of continuous, smooth noise that helps to generate visually cohesive and random-looking patterns. Unlike traditional random noise & value noise, Perlin …

  7. Perlin Noise - learn.64bitdragon.com

    Perlin noise produces good quality noise in any number of dimensions. Includes code in Python.

  8. Perlin Noise Explained - Cratecode

    A detailed explanation of Perlin Noise, its algorithm, and its applications in generative art and procedural generation.

  9. Perlin noise - Wikipedia, the free encyclopedia - Zubiaga

    Feb 15, 2009 · Perlin noise is a procedural texture primitive, used by visual effects artists to increase the appearance of realism in computer graphics. This is a type of Gradient noise. The …

  10. Perlin Noise | Academo.org - Free, interactive, education.

    Both are limited to a value between 0 and 1, but whereas white noise is truly random, Perlin noise results in a sequence of values that when, plotted along an x-axis, meander up and down …