🔲 Worley Noise
Cellular texture
Mode: F1
Output
Parameters
Controls
Stats
Points
0
Grid
0
Frame ms
0
Status
Ready
Info & Theory

Worley noise (cellular noise), introduced by Steven Worley in 1996, scatters feature points across the plane and colours each pixel by its distance to the nearest ones.

F1, F2 and combinations

  • F1 — distance to the nearest point: smooth cells.
  • F2 — distance to the second nearest.
  • F2 − F1 — thin ridges along cell borders: cracks.
  • F1 · F2 — a softer organic blend.

Distance metric

Euclidean gives round cells, Manhattan gives diamonds and Chebyshev gives squares. The metric reshapes the whole field at once.

Spatial grid (fast)

Points are bucketed into a grid. Each pixel only checks its own cell and the 8 neighbours, so the cost is roughly O(pixels) instead of O(pixels × points).

Voronoi link

Each point owns the pixels closest to it — a Voronoi cell. So F2 − F1 simply draws the Voronoi edges.

Frequently asked questions

What is Worley noise?

Worley noise, also called cellular noise, scatters feature points across the plane and colours each pixel by its distance to the nearest points. Steven Worley introduced it in 1996 for procedural stone, water, cell and crack textures.

What do F1 and F2 mean?

F1 is the distance from a pixel to its nearest feature point, F2 to the second nearest. Using F1 gives smooth cells; F2−F1 highlights the borders between cells as cracks; F1·F2 and other combinations give different organic looks.

How is this related to a Voronoi diagram?

Each feature point owns the region of pixels closest to it — that is exactly a Voronoi cell. The F2−F1 mode draws the Voronoi edges, so Worley noise is essentially a smooth, shaded Voronoi diagram.

What does the distance metric change?

Euclidean distance gives round, organic cells. Manhattan (taxicab) distance gives diamond-shaped cells aligned to the axes. Chebyshev distance gives square cells. Switching the metric reshapes every cell at once.

Why use a spatial grid?

Checking every pixel against every point would be very slow. Instead the feature points are bucketed into grid cells, and each pixel only checks the points in its own cell and the eight neighbours — making the cost roughly constant per pixel.

What does point density control?

Density sets how many feature points fall in each grid cell on average. Higher density means smaller, more numerous cells; lower density means large open cells with long cracks.

What is the animation doing?

When animation is on, each feature point drifts slowly around its home position, so the cells gently wobble and flow. The pattern is fully recomputed each frame from the moved points.

What are the palettes for?

The palette maps the distance value at each pixel to a colour. Grayscale shows the raw field; the stone, ember and ice palettes tint it to suggest rock, lava or frozen textures.

Is the texture seamless or tileable?

This demo renders a single window of the noise field and is not made tileable. Production Worley noise can be wrapped at the edges so it tiles, but that is left out here for clarity.

Where is Worley noise used in practice?

It is widely used in computer graphics for procedural textures, cloud and water shaders, caustics, cracked surfaces, and as a building block layered with Perlin noise in game and film rendering.

About this simulation

Written by MySimulator Team · Reviewed by MySimulator Editorial Review

Last updated: 5 July 2026

This simulator generates Worley noise — also called cellular noise — by scattering feature points across a grid and colouring every pixel according to its distance to the nearest ones. Because each pixel effectively belongs to whichever feature point is closest, the result is mathematically the same as a shaded Voronoi diagram, and it is a workhorse technique for procedural textures such as flagstones, cracked mud, and water caustics.

🔬 What it shows

A grid of randomly placed feature points, with every pixel shaded by its F1 (nearest) or F2 (second-nearest) distance, or by combinations such as F2−F1 or F1·F2, under a chosen distance metric and colour palette. F1 alone produces smooth rounded cells, while F2−F1 traces the thin ridges that sit exactly on the Voronoi boundary between neighbouring cells.

🎮 How to use

Switch the Mode between F1, F2, F2−F1 and F1·F2, and the Metric between Euclidean, Manhattan and Chebyshev to reshape the cells from round to diamond to square. The Density slider (3–24) controls how many feature points fall per grid cell, Drift speed animates them once you press Animate, Reseed randomises the point positions, and Save PNG exports the current frame.

💡 Did you know?

Worley noise was introduced by Steven Worley in his 1996 paper "A Cellular Texture Basis Function", as an alternative to Perlin noise that produces distinctly cell-like, organic patterns rather than smooth rolling hills — which is why it remains a standard choice for stone, scales, and biological textures in computer graphics.

Frequently asked questions

What is Worley noise?

Worley noise, or cellular noise, is a procedural texture technique that scatters a set of feature points through space and assigns each pixel a value based on its distance to the closest one or two points. It produces natural-looking cellular patterns such as cracked stone, water caustics, and organic cell structures rather than the smooth blobs typical of Perlin noise.

What do F1 and F2 mean in the Mode selector?

F1 is the distance from a pixel to its single nearest feature point, and F2 is the distance to the second-nearest one. Shading by F1 alone produces smooth, rounded cells; F2−F1 highlights the thin borders between neighbouring cells as crack-like ridges; and F1·F2 blends the two into a softer, more organic look.

How is Worley noise related to Voronoi diagrams?

Each feature point owns exactly the region of pixels that are closer to it than to any other point — which is the textbook definition of a Voronoi cell. Shading by F1 draws the interior of each Voronoi cell, while the F2−F1 mode draws precisely the edges of that same Voronoi diagram, so Worley noise is essentially a continuously shaded Voronoi tessellation.

What does the Density slider actually control?

Density sets the average number of feature points seeded into each grid cell before the nearest-distance search runs. A higher density packs in more points, giving smaller and more numerous cells, while a lower density spreads points further apart, producing large open cells separated by long cracks.

How do the Euclidean, Manhattan and Chebyshev metrics change the pattern?

Euclidean distance is straight-line distance and produces the classic round, organic cells. Manhattan distance sums the horizontal and vertical offsets, which turns the cell boundaries into diamond shapes. Chebyshev distance takes the larger of the horizontal or vertical offset, which squares off the cells into blocky, grid-aligned shapes.