Feature-based adaptive texture visualization for vector field

Steerable texture synthesis for vector field visualization

Fast texture based algorithms for vector field visualization

Acknowledgements The work described in this thesis has been carried out from 1995 to 1998 at the department of Scientific Visualization at the Konrad-Zuse-Zentrum Berlin (ZIB). First of all, I would like to thank my tutors Prof. Dr. Peter Deuflhard and Hans-Christian Hege for the opportunity to graduate. They introduced me into an interesting new field between mathematics, computer science, and...

Global, geometric, and feature-based techniques for vector field visualization

Vector field visualization techniques are subdivided into three categories: global, geometric, and feature-based techniques. We describe each category, and we present some related work and an example in each category from our own recent research. Spot Noise is a texture synthesis technique for global visualization of vector fields on 2D surfaces. Deformable surfaces is a generic technique for e...

Animation of Orthogonal Texture-Based Vector Field Visualization

This paper introduces orthogonal vector field visualization on 2D manifolds: a representation by lines that are perpendicular to the input vector field. Line patterns are generated by line integral convolution (LIC). This visualization is combined with animation based on motion along the vector field. This decoupling of the line direction from the direction of animation allows us to choose the ...

Vector field visualization using Markov Random Field texture synthesis

Vector field visualization generates an image to convey the information existing in the data. We use Markov Random Field texture synthesis methods to generate the visualization from a set of example textures. The examples textures are chosen according to the vector data for each pixel of the output. This leads to dense visualizations with arbitrary example textures.