The 3D Noise Texmap plugin includes well-known noise patterns such as Perlin, Simplex, and Worley (Voronoi). It offers two texture maps: ProSimplex and ProVoronoi. Both maps support a variety of fractal options like fBm, Turbulence, Ridged Multifractal, and more. With options for distortion and parameter mapping from Size to Fractal Octaves, you can create an infinite number of unique patterns.

Parameters

General Parameters

  • Size: Defines the dimensions of the noise table. This parameter can be mapped with other textures.
  • Threshold Low / High: Stretches the dynamic range to fill 0 to 1 when the noise value is between the Low and High thresholds. These parameters can also be mapped with other textures.

Colors

  • Color #1 / Color #2: Opens the Color Selector to choose one of the two primary noise colors. Intermediate colors are generated between the selected colors. These colors can be mapped with bitmaps or procedural maps, and activating the checkboxes makes these maps active.

UVW Distort

  • Options: Normal, Radial

Installation

  1. Copy the file “SigerNoise_xxxx.dlt” to the MAXROOT\plugins directory (delete any older version of the file if present).
  2. Use the appropriate file for your 3ds Max version:
    • SigerNoise_2013.dlt: Compatible with 3ds Max 2013/2014
    • SigerNoise_2015.dlt: Compatible with 3ds Max 2015/2016
    • SigerNoise_2017.dlt: Compatible with 3ds Max 2017
    • SigerNoise_2018.dlt: Compatible with 3ds Max 2018

ProSimplex

The ProSimplex texmap includes two noise types: Perlin (2D, 3D, 4D) and Simplex (2D, 3D, 4D).

  • Perlin Noise: Developed by Ken Perlin in 1982, this type of gradient noise is widely recognized for its quality.
  • Simplex Noise: Created by Ken Perlin in 2001, it offers similar results to Perlin Noise but with reduced computational requirements. Simplex divides the N-dimensional space into triangles, reducing the number of data points. The visual results are similar to Perlin Noise.
  • Phase: Offset in the fourth dimension (w), representing the “location” in time.

ProVoronoi

  • Worley Noise: Also known as Cell Noise or Voronoi Noise, this type computes the distance to randomly distributed points, weighting each pixel’s lightness by the distance to the nearest point.
  • Distance Metric: Six options to measure distances to neighboring cells:
    • Euclidean: Computes the Euclidean distance to the nearest points, resulting in pointy shapes.
    • Euclidean Squared: Similar to Euclidean but with rounder shapes.
    • Manhattan: Computes the distance based on grid-like paths.
    • Chebyshev: Similar to Manhattan but rotated 45 degrees.
    • Minkowski 0.5: Generalizes both Euclidean and Manhattan distances.
    • Minkowski 4: Another variation of the Minkowski distance.
  • Feature Weights: F1, F2, F3, F4 represent the Worley constants used to calculate cell distances based on the selected Distance Metric. Adjusting these values affects the final texture. Parameters can be mapped.

Noise Fractal Types

  • Fractal
  • Turbulence (Billow)
  • fBm
  • fBm Turbulence
  • Hetero Terrain
  • Hybrid MultiFractal
  • Ridged MultiFractal
  • Octave: Controls the number of times the noise pattern is overlaid on itself.
  • Offset: Adjusts light intensity.
  • Gain: Determines the range of values created by the function.
  • Lacunarity: Multiplier for frequency increase for each successive octave.
  • Exponent: Fractal increment parameter H (Hurst exponent), affecting noise smoothness.