Adaptive Splatting for Specular to Diffuse Light Transport

Abstract

We present an extension to existing techniques to provide for more accurate resolution of specular to diffuse transfer within a global illumination framework. In particular this new model is adaptive with a view to capturing high frequency phenomena such as caustic curves in sharp detail and yet allowing for low frequency detail without compromising noise levels and aliasing artefacts. A 2-pass ray-tracing algorithm is used, with an adaptive light-pass followed by a standard eye-pass. During the lightpass, rays are traced from the light sources (essentially sampling the wavefront radiating from the sources), each carrying a fraction of the total power per wavelength of the source. The interactions of these rays with diffuse surfaces are recorded in illumination-maps, as first proposed by Arvo[Ar86]. The key to reconstructing the intensity gradients due to this light-pass lies in the construction of the illumination maps. We record the power carried by the ray as a splat of energy flux, deposited on the surface using a Gaussian distribution kernel. The kernel of the splat is adaptively scaled according to an estimation of the wavefront divergence or convergence, thus resolving sharp intensity gradients in regions of high wavefront convergence and smooth gradients in areas of divergence. The 2nd pass eye-trace modulates the surfaces radiance according to the power stored in the illumination map in order to include the specular to diffuse light modelled during the first pass.