Advanced Volume Illumination with Unconstrained Light Source Positioning

Abstract

Advanced volume visualization techniques are important for both visual arts and visualization. They allow efficient generation of visual effects and the visualization of scientific data obtained by tomography or numerical simulation. More natural illumination, which can be achieved with more advanced models, supports spatial comprehension and even improves shape perception.1 Whereas in polygonal computer graphics, advanced shading models are already established, volume visualization often employs local Phong-based illumination models. So, artists must extract polygonal surfaces from the volumetric data to benefit from more advanced shading effects when generating visual media. However, users can exploit the full benefit of volumetric data only when they can change the most relevant rendering parameters, such as the transfer function or the lighting setup. This enables artists to interactively explore the visual space and quickly decide which images convey the most information. Such a proceeding improves the visual design process and allows easy generation of production-ready visual media. Thus, laypeople could access an interactive application with which they can explore the volumetric data to more deeply understand the involved structures. To support this scenario with advanced lighting requires appropriate illumination models, which can be realized with current GPUs. Because advanced illumination models usually take neighboring structures into account during shading, this results in more complex operations, which make obtaining the desired interactive frame rates even more challenging. Here, we present an advanced volumetric illumination model that approximates physically based light transport more convincingly than standard gradient-based shading. This model takes neighboring structures into account by incorporating shadowing and scattering (see the “Scattering” sidebar), leading to more natural lighting and thus improved depth perception.