Adaptive transfer of color from images to maps and visualizations

ABSTRACT

Because crafting attractive and effective colors from scratch is a high-effort and time-consuming process in map and visualization design, transferring color from an inspiration source to maps and visualizations is a promising technique for both novices and experts. To date, existing image-to-image color transfer methods suffer from ambiguities and inconsistencies; no computational approach is available to transfer color from arbitrary images to vector maps. To fill this gap, we propose a computational method that transfers color from arbitrary images to a vector map. First, we classify reference images into regions with measures of saliency. Second, we quantify the communicative quality and esthetics of colors in maps; we then transform the problem of color transfer into a dual-objective, multiple-constraint optimization problem. We also present a solution method that can create a series of optimal color suggestions and generate a communicative quality-esthetic compromise solution. We compare our method with an image-to-image method based on two sample maps and six reference images. The results indicate that our method is adaptive to mapping scales, themes, and regions. The evaluation also provides preliminary evidence that our method can achieve better communicative quality and harmony.

KEYWORDS:

• Color transfer
• map design
• communicative quality
• esthetic
• color harmony

Acknowledgments

We would like to thank Robert Roth for his helpful feedback on very early stages of this idea. We would also like to thank two anonymous reviewers for their useful comments.

Data availability statement

The source code and test data are available as free and open-source software (FOSS) for reproducibility and extension at: https://doi.org/10.5281/zenodo.4727805. The data is licensed using the MIT License.

Disclosure statement

The author reports no potential conflicts of interest.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant [41971417, 41631175, 41930104].