Modeling multiple scattering in microfacet theory is considered an important open problem because a non-negligible portion of the energy leaving rough surfaces is due to paths that bounce multiple times. In this paper we derive the missing multiple-scattering components of the popular family of BSDFs based on the Smith microsurface model. Our derivations are based solely on the original assumptions of the Smith model. We validate our BSDFs using raytracing simulations of explicit random Beckmann surfaces. Our main insight is that the microfacet theory for surfaces with the Smith model can be derived as a special case of the microflake theory for volumes, with additional constraints to enforce the presence of a sharp interface, i.e. to transform the volume into a surface. We derive new free-path distributions and phase functions such that plane-parallel scattering from a microvolume with these distributions exactly produces the BSDF based on the Smith microsurface model, but with the addition of higher-order scattering. With this new formulation, we derive multiple-scattering micro-facet BSDFs made of either diffuse, conductive, or dielectric material. Our resulting BSDFs are reciprocal, energy conserving, and support popular anisotropic parametric normal distribution functions such as Beckmann and GGX. While we do not provide closed-form expressions for the BSDFs, they are mathematically well-defined and can be evaluated at arbitrary precision. We show how to practically use them with Monte Carlo physically based rendering algorithms by providing analytic importance sampling and unbiased stochastic evaluation. Our implementation is analytic and does not use per-BSDF precomputed data, which makes our BSDFs usable with textured albedos, roughness, and anisotropy.
Figure 1: Top-left: rendering a voxelized forest at decreasing levels of detail (left to right). Bottom-right: visualization of the voxel structure at the matching resolutions. We use the SGGX microflake distribution to represent volumetric anisotropic materials. Our representation supports downscaling and interpolation, resulting in smooth and antialiased renderings at multiple scales. AbstractWe introduce the Symmetric GGX (SGGX) distribution to represent spatially-varying properties of anisotropic microflake participating media. Our key theoretical insight is to represent a microflake distribution by the projected area of the microflakes. We use the projected area to parameterize the shape of an ellipsoid, from which we recover a distribution of normals. The representation based on the projected area allows for robust linear interpolation and prefiltering, and thanks to its geometric interpretation, we derive closed form expressions for all operations used in the microflake framework.We also incorporate microflakes with diffuse reflectance in our theoretical framework. This allows us to model the appearance of rough diffuse materials in addition to rough specular materials. Finally, we use the idea of sampling the distribution of visible normals to design a perfect importance sampling technique for our SGGX microflake phase functions. It is analytic, deterministic, simple to implement, and one order of magnitude faster than previous work.
Figure 1: A high-quality animated production model (Ptex T-rex model c Walt Disney Animation Studios.) rendered in real time under directional and environment lighting using LEADR mapping on an NVidia GTX 480 GPU. The surface appearance is preserved at all scales, using a single shading sample per pixel. Combined with adaptive GPU tessellation, our method provides the fastest, seamless, and antialiased progressive representation for displaced surfaces. AbstractWe present Linear Efficient Antialiased Displacement and Reflectance (LEADR) mapping, a reflectance filtering technique for displacement mapped surfaces. Similarly to LEAN mapping, it employs two mipmapped texture maps, which store the first two moments of the displacement gradients. During rendering, the projection of this data over a pixel is used to compute a noncentered anisotropic Beckmann distribution using only simple, linear filtering operations. The distribution is then injected in a new, physically based, rough surface microfacet BRDF model, that includes masking and shadowing effects for both diffuse and specular reflection under directional, point, and environment lighting. Furthermore, our method is compatible with animation and deformation, making it extremely general and flexible. Combined with an adaptive meshing scheme, LEADR mapping provides the very first seamless and hardware-accelerated multi-resolution representation for surfaces. In order to demonstrate its effectiveness, we render highly detailed production models in real time on a commodity GPU, with quality matching supersampled ground-truth images.
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