Volume rendering with splatting most commonly decomposes a volume dataset into a field of overlapping radial basis function (RBF) kernels, such as Gaussians. The rendering effort is directly related to the number of RBFs in the volume and the degree of RBF overlap in the rasterization phase. Much work has been done that seeks to lower the number of RBFs by replacing a neighborhood of kernels wi...

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...

In this paper, we present a framework for high quality splatting based on elliptical Gaussian kernels. To avoid aliasing artifacts, we introduce the concept of a resampling filter, combining a reconstruction kernel with a low-pass filter. Because of the similarity to Heckbert’s EWA (elliptical weighted average) filter for texture mapping, we call our technique EWA splatting. Our framework allow...