Smoothstep

A plot of the smoothstep(x) and smootherstep(x) functions, using 0 as the left edge and 1 as the right edge.

Smoothstep is an interpolation function commonly used in computer graphics[1][2] and video game engines.[3]

The function depends on two parameters, the "left edge" and the "right edge", with the left edge being assumed smaller than the right edge. The function takes a real number x as input and outputs 0 if x is less than or equal to the left edge, 1 if x is greater than or equal to the right edge, and smoothly interpolates between 0 and 1 otherwise. The slope of the smoothstep function is zero at both edges. This makes it easy to create a sequence of transitions using smoothstep to interpolate each segment rather than using a more sophisticated or expensive interpolation technique.

As pointed out in MSDN and OpenGL documentation, smoothstep implements cubic Hermite interpolation after doing a clamp:

where we assume that the left edge is 0, the right edge is 1, and 0 ≤ x ≤ 1.

A C/C++ example implementation provided by AMD[4] follows.

float smoothstep(float edge0, float edge1, float x)
{
    // Scale, bias and saturate x to 0..1 range
    x = clamp((x - edge0)/(edge1 - edge0), 0.0, 1.0); 
    // Evaluate polynomial
    return x*x*(3 - 2*x);
}

Variations

Ken Perlin suggests[5] an improved version of the smoothstep function which has zero 1st and 2nd order derivatives at x=0 and x=1:

C/C++ reference implementation:

float smootherstep(float edge0, float edge1, float x)
{
    // Scale, and clamp x to 0..1 range
    x = clamp((x - edge0)/(edge1 - edge0), 0.0, 1.0);
    // Evaluate polynomial
    return x*x*x*(x*(x*6 - 15) + 10);
}

Origin

3rd order equation

We start with a generic third order polynomial function and its first derivative:

Applying the desired values for the function at both endpoints we get:

Applying the desired values for the first derivative of the function at both endpoints we get:

Solving the system of 4 unknowns formed by the last 4 equations we obtain the values of the polynomial coefficients:

Introducing these coefficients back into the first equation gives the third order smoothstep function:

5th order equation

We start with a generic fifth order polynomial function, its first derivative and its second derivative:

Applying the desired values for the function at both endpoints we get:

Applying the desired values for the first derivative of the function at both endpoints we get:

Applying the desired values for the second derivative of the function at both endpoints we get:

Solving the system of 6 unknowns formed by the last 6 equations we obtain the values of the polynomial coefficients:

Introducing these coefficients back into the first equation gives the fifth order smootherstep function:

7th order equation

Also called "smootheststep", the 7th order equation was derived by Kyle McDonald and first posted to Twitter[6] with a derivation on GitHub:[7]

Generalization of higher-order equations

All smoothstep equations can be generalized as:

where a determines the order of the resulting polynomial equation, with the order being calculated as 2a - 1. Evaluating this function for different values of a gives:

For any value a where a > 0, this generalization will smoothly interpolate from 0 to 1 for any value x on the interval 0 ≤ x ≤ 1 while retaining the property Sa(0.5) = 0.5.

References

External links

This article is issued from Wikipedia - version of the 10/10/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.