Wavelet noise explained

See also: Wavelet.

Wavelet noise is an alternative to Perlin noise which reduces the problems of aliasing and detail loss that are encountered when Perlin noise is summed into a fractal.

Algorithm detail

The basic algorithm for 2-dimensional wavelet noise is as follows:

• Create an image,

R , filled with uniform white noise.

• Downsample

R to half-size to create R ^{\downarrow} , then upsample it back up to full size to create R ^{\downarrow\uparrow} .

• Subtract

R ^{\downarrow\uparrow} from R to create the end result, N .This results in an image that contains all the information that cannot be represented at half-scale. From here, N can be used similarly to Perlin noise to create fractal patterns.

External links

• Wavelet Noise Paper at pixar.com.