11.3 Phase Functions

Just as there is a wide variety of BSDF models that describe scattering from surfaces, many phase functions have also been developed. These range from parameterized models (which can be used to fit a function with a small number of parameters to measured data) to analytic models that are based on deriving the scattered radiance distribution that results from particles with known shape and material (e.g., spherical water droplets).

In most naturally occurring media, the phase function is a 1D function of the angle between the two directions and ; these phase functions are often written as . Media with this type of phase function are called isotropic or symmetric because their response to incident illumination is (locally) invariant under rotations. In addition to being normalized, an important property of naturally occurring phase functions is that they are reciprocal: the two directions can be interchanged and the phase function’s value remains unchanged. Note that symmetric phase functions are trivially reciprocal because .

In anisotropic media that consist of particles arranged in a coherent structure, the phase function can be a 4D function of the two directions, which satisfies a more involved kind of reciprocity relation. Examples of this are crystals or media made of coherently oriented fibers; the “Further Reading” discusses these types of media further.

In a slightly confusing overloading of terminology, phase functions themselves can be isotropic or anisotropic as well. Thus, we might have an anisotropic phase function in an isotropic medium. An isotropic phase function describes equal scattering in all directions and is thus independent of either of the two directions. Because phase functions are normalized, there is only one such function:

The PhaseFunction class defines the PhaseFunction interface. Only a single phase function is currently provided in pbrt, but we have used the TaggedPointer machinery to make it easy to add others. Its implementation is in the file base/medium.h.

The p() method returns the value of the phase function for the given pair of directions. As with BSDFs, pbrt uses the convention that the two directions both point away from the point where scattering occurs; this is a different convention from what is usually used in the scattering literature (Figure 11.13).

It is also useful to be able to draw samples from the distribution described by a phase function. PhaseFunction implementations therefore must provide a Sample_p() method, which samples an incident direction given the outgoing direction and a sample value in .

Phase function samples are returned in a structure that stores the phase function’s value p, the sampled direction wi, and the PDF pdf.

An accompanying PDF() method returns the value of the phase function sampling PDF for the provided directions.

11.3.1 The Henyey–Greenstein Phase Function

A widely used phase function was developed by Henyey and Greenstein (1941). This phase function was specifically designed to be easy to fit to measured scattering data. A single parameter (called the asymmetry parameter) controls the distribution of scattered light: ^†

The HenyeyGreenstein() function implements this computation.

The asymmetry parameter in the Henyey–Greenstein model has a precise meaning. It is the integral of the product of the given phase function and the cosine of the angle between and and is referred to as the mean cosine. Given an arbitrary phase function , the value of can be computed as ^†

Thus, an isotropic phase function gives , as expected.

Any number of phase functions can satisfy this equation; the value alone is not enough to uniquely describe a scattering distribution. Nevertheless, the convenience of being able to easily convert a complex scattering distribution into a simple parameterized model is often more important than this potential loss in accuracy.

More complex phase functions that are not described well with a single asymmetry parameter can often be modeled by a weighted sum of phase functions like Henyey–Greenstein, each with different parameter values:

where the weights sum to one to maintain normalization. This generalization is not provided in pbrt but would be easy to add.

Figure 11.14 shows plots of the Henyey–Greenstein phase function with varying asymmetry parameters. The value of for this model must be in the range . Negative values of correspond to back-scattering, where light is mostly scattered back toward the incident direction, and positive values correspond to forward-scattering. The greater the magnitude of , the more scattering occurs close to the or directions (for back-scattering and forward-scattering, respectively). See Figure 11.15 to compare the visual effect of forward- and back-scattering.

The HGPhaseFunction class implements the Henyey–Greenstein model in the context of the PhaseFunction interface.

Its only parameter is , which is provided to the constructor and stored in a member variable.

Evaluating the phase function is a simple matter of calling the HenyeyGreenstein() function.

It is possible to sample directly from the Henyey–Greenstein phase function’s distribution. This operation is provided via a stand-alone utility function. Because the sampling algorithm is exact and because the Henyey–Greenstein phase function is normalized, the PDF is equal to the phase function’s value for the sampled direction.

The PDF for the Henyey–Greenstein phase function is separable into and components, with as usual. The main task is to sample . With pbrt’s convention for the orientation of direction vectors, the distribution for is

if ; otherwise, gives a uniform sampling over the sphere of directions.

The values specify a direction with respect to a coordinate system where wo is along the axis. Therefore, it is necessary to transform the sampled vector to wo’s coordinate system before returning it.

The HGPhaseFunction sampling method is now easily implemented.

Because sampling is exact and phase functions are normalized, its PDF() method just evaluates the phase function for the given directions.