The plugin contains two texture maps: ProSimplex and ProVoronoi. Both support a large number of fractal options such as fBm, Turbulence, Ridged Multifractal, etc..
With distortion and mapping of all parameters from Size to Fractal Octaves you can get an infinite number of different patterns.
|3ds Max 2024||1.1.2||Download|
|3ds Max 2023||1.1.1||Download|
|3ds Max 2022||1.0.7||Download|
|3ds Max 2017 - 2021||1.0.6||Download|
|3ds Max 2013 - 2016||Legacy - 1.0.4||Download|
Size – The dimensions of the noise table. Parameter can be mapped with other texture.
Threshold Low / High – When the noise value is above the Low threshold and below the High threshold, the dynamic range is stretched to fill 0 to 1. Parameters can be mapped with other texture.
Color #1 / Color #2 – Display the Color Selector so you can choose one or the other of the two principal noise colors. Intermediate color values are generated from the two colors you select. Colors can be mapped: select the bitmaps or procedural maps to appear in one or the other noise color, turn on the checkboxes to make the maps active.
UVW distort – Two options: Normal, Radial.
ProSimplex texmap contain two noise types: Perlin (2D, 3D, 4D) and Simplex (2D, 3D, 4D).
Perlin Noise is the award winning type of gradient noise developed by Ken Perlin in 1982.
Simplex Noise developed by Ken Perlin in 2001 has similar results to Perlin Noise with less computational requirements than Perlin. The idea of Simplex is to divide the N dimensional space into triangles that reduces the number of data points. In Perlin noise we would find the cube that the point we are given in resides and find the points related. Visually the result is not much different from Perlin Noise.
Phase – offset in fourth dimension (w) – the “location” in time.
Worley Noise also known as Cell Noise or occasionally Voronoi Noise – computing the distance to randomly distributed points, and weighting the lightness of the each pixel by the distance from the closest point.
Distance Metric – 6 distance metric options. The means to measure distances to neighboring cells. F. e., Manhattan distance gives more rectangular shapes and Euclidean distance gives more spherical shapes.
Euclidean. Computes the Euclidean distance to the nearest points. It looks a bit more pointy than Euclidean Squared distance.
Euclidean Squared. Computes the Euclidean Squared distance to the nearest points. It looks rounder than pure Euclidean distance.
Manhattan. Inspired by the grid-like organization of Manhattan, this is distance to the nearest points when you can only travel around the cell’s boundaries.
Chebyshev. Also known as the Chessboard Distance, it is somewhat similar to the Manhattan distance, but with 45 degrees rotation.
Minkowski 0.5. Minkowski – a generalization of both Euclidean and Manhattan distance (Minkowski Exponent e = 0.5).
Minkowski 4. (Minkowski Exponent e = 4).
Feature Weights – F1, F2, F3, F4
Represent the values of the four Worley constants, which are used to calculate the distances between each cell in the texture based on the Distance metric. Adjusting these values can have some interesting effects on the end result. Parameters can be mapped.
Some examples. Distance Metric: Euclidean Squared.
Available seven fractal types:
– Turbulence (Billow)
– fBm Turbulence
– Hetero Terrain
– Hybrid MultiFractal
– Ridged MultiFractal
Octave – controls the number of times the original noise pattern is overlayed on itself.
Offset – light intensity.
Gain – determines the range of values created by the function. The higher the number, the greater the range.
Lacunarity – a multiplier that determines how quickly the frequency (size) increases for each successive octave in a noise function.
The frequency of each successive octave is equal to the product of the previous octave’s frequency and the lacunarity value.
i.e. Lacunarity = 2.0 –> Scale = 1/2 original.
Exponent – the fractal increment parameter H (Hurst exponent). The higher H becomes, the more smoother the noise will be.
Created by Siger (Regimantas Valiukas | Siger Studio), 2015-2023
– Jerry Ylilammi (BerconNoise)
– Ken Perlin (Perlin/Simplex noise)
– Stefan Gustavson (C++ implementation of Perlin and Simplex noises)
– Steven Worley (Worley noise and C implementation of it)
– Blender team (Blender noise/cellnoise/fractals)
– John Burnett (Distortions max shadecontext implementation)