Automatic Improvement of Continuous Colormaps in Euclidean Colorspaces

Abstract
Colormapping is one of the simplest and most widely used data visualization methods within and outside the visualization community. Uniformity, order, discriminative power, and smoothness of continuous colormaps are the most important criteria for evaluating and potentially improving colormaps. We present a local and a global automatic optimization algorithm in Euclidean color spaces for each of these design rules in this work. As a foundation for our optimization algorithms, we used the CCC-Tool colormap specification (CMS); each algorithm has been implemented in this tool. In addition to synthetic examples that demonstrate each method's effect, we show the outcome of some of the methods applied to a typhoon simulation.
Description

        
@article{
10.1111:cgf.14313
, journal = {Computer Graphics Forum}, title = {{
Automatic Improvement of Continuous Colormaps in Euclidean Colorspaces
}}, author = {
Nardini, Pascal
and
Chen, Min
and
Böttinger, Michael
and
Scheuermann, Gerik
and
Bujack, Roxana
}, year = {
2021
}, publisher = {
The Eurographics Association and John Wiley & Sons Ltd.
}, ISSN = {
1467-8659
}, DOI = {
10.1111/cgf.14313
} }
Citation
Collections