Sparse Texture Visualization for Vector Fields Based on Cool/Warm Illumination Model

Texture-based methods play a very important role for visualizing 3D flows.However, many existing methods suffer a difficulty that can't express the flow direction concretely.To overcome this problem, we present in this paper two novel illuminating methods which are based on the classical cool/warm illumination model.First, we present the Halton sequence and Gauss filter to produce sparse noises, which are the input data for the next LIC calculation.Then we introduce some concepts, such as the cool/warm source and the distance factor, to build our cool/warm illumination models.One of the method expresses the flow direction globally through the distance factor value.Another method controls the color change from warm to cool for each texture fragment by analyzing the Gauss noises.The experimental results show that our methods can reflect the concrete vector direction clearly in the global and local manners.