Regularised Anisotropic Nonlinear Diffusion for Rendering Refraction in Volume Graphics

Abstract

Rendering refraction in volume graphics requires smoothly distributed normals to synthesise good quality visual representations. Such refractive visualisation is more susceptible to noise in the data than visualisations that do not involve refraction. In this paper, we addresses the need for improving the continuity of voxel gradients in discretely sampled volume datasets using nonlinear diffusion methods, which was originally developed for image denoising. We consider the necessity for minimising unnecessary geometrical distortion, detail the functional specification of a volumetric filter for regularised anisotropic nonlinear diffusion (R-ANLD), discuss the further improvements of the filter, and compare the efficacy of the filter with an anisotropic nonlinear diffusion (ANLD) filter as well as a Gaussian filter and a linear diffusion filter. Our results indicate that it is possible to make significant improvements in image quality in refractive rendering without excessive distortion.