Simulation noise

Simulation noise is a function that creates a divergence-free vector field. This signal can be used in artistic simulations for the purposes of increasing the perception of extra detail. The function can be calculated in three dimensions by dividing the space into a regular lattice grid. With each edge is associated a random value, indicating a rotational component of material revolving around the edge. By following rotating material into and out of faces, one can quickly sum the flux passing through each face of the lattice. Flux values at lattice faces are then interpolated to create a field value for all positions.

Perlin noise is the earliest form of lattice noise, which has become very popular in computer graphics. Perlin Noise is not suited for simulation because it is not divergence-free.

Noises based on lattices, such as simulation noise and Perlin noise, are often calculated at different frequencies and summed together to form band-limited fractal signals.

Other approaches developed later that use vector calculus identities to produce divergence free fields, such as "Curl-Noise" as suggested by Robert Bridson, and "Divergence-Free Noise" due to Ivan DeWolf. These often require calculation of lattice noise gradients, which sometimes are not readily available. A naive implementation would call a lattice noise function several times to calculate its gradient, resulting in more computation than is strictly necessary. Unlike these noises, simulation noise has a geometric rationale in addition to its mathematical properties. It simulates vortices scattered in space, to produce its pleasing aesthetic.

## References

## Further reading

* Patel, M & Taylor, N. December 2005. Simple Divergence-Free Fields for Artistic Simulation. Journal of Graphics Tools, Volume 10, Number 4.

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Noise (physics and telecommunications)

General|

* Acoustic quieting
* Distortion
* Noise cancellation
* Noise control
* Noise measurement
* Noise power
* Noise reduction
* Noise temperature
* Phase distortion

Noise in...|

* Audio
* Buildings
* Electronics
* Environment
* Government regulation
* Human health
* Images
* Radio
* Rooms
* Ships
* Sound masking
* Transportation
* Video

Class of noise|

* Additive white Gaussian noise (AWGN)
* Atmospheric noise
* Background noise
* Brownian noise
* Burst noise
* Cosmic noise
* Flicker noise
* Gaussian noise
* Grey noise
* Jitter
* Johnson–Nyquist noise (thermal noise)
* Pink noise
* Quantization error (or q. noise)
* Shot noise
* White noise
* Coherent noise
* Value noise
* Gradient noise
* Worley noise

Engineering
terms|

* Channel noise level
* Circuit noise level
* Effective input noise temperature
* Equivalent noise resistance
* Equivalent pulse code modulation noise
* Impulse noise (audio)
* Noise figure
* Noise floor
* Noise shaping
* Noise spectral density
* Noise, vibration, and harshness (NVH)
* Phase noise
* Pseudorandom noise
* Statistical noise

Ratios|

* Carrier-to-noise ratio (C/N)
* Carrier-to-receiver noise density (C/kT)
* dBrnC
* Eb/N0 (energy per bit to noise density)
* Es/N0 (energy per symbol to noise density)
* Modulation error ratio (MER)
* Signal, noise and distortion (SINAD)
* Signal-to-interference ratio (S/I)
* Signal-to-noise ratio (S/N, SNR)
* Signal-to-noise ratio (imaging)
* Signal to noise plus interference (SNIR)
* Signal-to-quantization-noise ratio (SQNR)
* Contrast-to-noise ratio (CNR)

Related topics|

* List of noise topics
* Acoustics
* Colors of noise
* Interference (communication)
* Noise generator
* Radio noise source
* Spectrum analyzer
* Thermal radiation

Denoise
methods|

| General|

* Low-pass filter
* Median filter
* Total variation denoising
* Wavelet denoising

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2D (Image)|

* Gaussian blur
* Anisotropic diffusion
* Bilateral filter
* Non-local means
* Block-matching and 3D filtering (BM3D)
* Shrinkage Fields
* Denoising autoencoder (DAE)
* Deep Image Prior

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Procedural coherent noise

Approach|

| Lattice based|

| Gradient noise|

* Simplex noise
* OpenSimplex noise
* Perlin noise
* Wavelet noise

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Value noise|

* Value noise

Point based|

* Worley noise (Voronoi/Cellular noise)

Applications|

* Procedural generation
* Computer graphics
* Video games
* Fractal landscapes

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