Inigo's experiments with Voronoi didn't stop there. In 2014 he wrote this nice article about what he calls [voro-noise](http://www.iquilezles.org/www/articles/voronoise/voronoise.htm), an function that allows a gradual blend between regular noise and voronoi. In his words:
Inigo's experiments with Voronoi didn't stop there. In 2014 he wrote this nice article about what he calls [voro-noise](http://www.iquilezles.org/www/articles/voronoise/voronoise.htm), a function that allows a gradual blend between regular noise and voronoi. In his words:
*"Despite this similarity, the fact is that the way the grid is used in both patterns is different. Noise interpolates/averages random values (as in value noise) or gradients (as in gradient noise), while Voronoi computes the distance to the closest feature point. Now, smooth-bilinear interpolation and minimum evaluation are two very different operations, or... are they? Can they perhaps be combined in a more general metric? If that was so, then both Noise and Voronoi patterns could be seen as particular cases of a more general grid-based pattern generator?"*
*"Despite this similarity, the fact is that the way the grid is used in both patterns is different. Noise interpolates/averages random values (as in value noise) or gradients (as in gradient noise), while Voronoi computes the distance to the closest feature point. Now, smooth-bilinear interpolation and minimum evaluation are two very different operations, or... are they? Can they perhaps be combined in a more general metric? If that was so, then both Noise and Voronoi patterns could be seen as particular cases of a more general grid-based pattern generator?"*