SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Procedural annotation of uncertain information
Proceedings of the conference on Visualization '00
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Glyphs for Visualizing Uncertainty in Vector Fields
IEEE Transactions on Visualization and Computer Graphics
Color Sequences for Univariate Maps: Theory, Experiments and Principles
IEEE Computer Graphics and Applications
Visualizing spatial distribution data sets
VISSYM '03 Proceedings of the symposium on Data visualisation 2003
Visualizing Large-Scale Uncertainty in Astrophysical Data
IEEE Transactions on Visualization and Computer Graphics
Uncertainty Visualization in Medical Volume Rendering Using Probabilistic Animation
IEEE Transactions on Visualization and Computer Graphics
Revealing uncertainty for information visualization
Information Visualization
Procedural Texture Synthesis for Zoom-Independent Visualization of Multivariate Data
Computer Graphics Forum
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We present a new method to visualize uncertain scalar data fields by combining color scale visualization techniques with animated, perceptually adapted Perlin noise. The parameters of the Perlin noise are controlled by the uncertainty information to produce animated patterns showing local data value and quality. In order to precisely control the perception of the noise patterns, we perform a psychophysical evaluation of contrast sensitivity thresholds for a set of Perlin noise stimuli. We validate and extend this evaluation using an existing computational model. This allows us to predict the perception of the uncertainty noise patterns for arbitrary choices of parameters. We demonstrate and discuss the efficiency and the benefits of our method with various settings, color maps and data sets.