noise_worley {ambient} | R Documentation |
Worley noise, sometimes called cell (or cellular) noise, is quite distinct due to it's kinship to voronoi tesselation. It is created by sampling random points in space and then for any point in space measure the distance to the closest point. The noise can be modified further by changing either the distance measure or by combining multiple distances. The noise algorithm was developed by Steven Worley in 1996 and has been used to simulated water and stone textures among other things.
noise_worley(dim, frequency = 0.01, distance = "euclidean", value = "cell", distance_ind = c(1, 2), jitter = 0.45, pertubation = "none", pertubation_amplitude = 1)
dim |
The dimensions (height, width, (and depth)) of the noise to be generated. The length determines the dimensionality of the noise. |
frequency |
Determines the granularity of the features in the noise. |
distance |
The distance measure to use, either |
value |
The noise value to return. Either
|
distance_ind |
Reference to the nth and mth closest points that should
be used when calculating |
jitter |
The maximum distance a point can move from its start position during sampling of cell points. |
pertubation |
The pertubation to use. Either |
pertubation_amplitude |
The maximal pertubation distance from the
origin. Ignored if |
If length(dim) == 2
a matrix, if length(dim) == 3
a 3-dimensional
array.
Worley, Steven (1996). A cellular texture basis function. Proceedings of the 23rd annual conference on computer graphics and interactive techniques. pp. 291–294. ISBN 0-89791-746-4
# Basic use noise <- noise_worley(c(100, 100)) image(noise, col = grey.colors(256, 0, 1))