Open Access

Detlev Stalling

• In this thesis we develop new methods for visualizing vector fields which specifically address three design goals: accuracy, performance, and cognition. Our methods will be general-purpose and can be applied to arbitrary vector fields in two- and three-dimensional space. The methodology behind our approach is {\em texture-based visualization}. Texture-based visualization methods imitate techniques known from experimental flow visualization, namely, the observation of randomly dispersed particles or dye injection patterns. Instead of depicting individual lines or symbols, a contiguous high-resolution image or texture is generated. This texture clearly reveals the directional structure of the field. In this way intuitive insight can be obtained and even small details of the field become visible. However, it remains unclear what kind of textures are best suited for our purpose. How do we generate them? Can we apply these methods in three-dimensional space? In particular, we focus on a technique known as {\em line integral convolution} or LIC. This method turns out to be quite versatile and well-suited for visualizing many interesting vector fields. LIC images display the integral curves or field lines of a vector field at high spatial resolution. Although conceptually quite simple, line integral convolution implies a number of interesting mathematical and algorithmic questions.