A Survey of Colormaps in Visualization

Journal Article · Mon Aug 01 00:00:00 EDT 2016 · IEEE Transactions on Visualization and Computer Graphics

DOI:https://doi.org/10.1109/TVCG.2015.2489649· OSTI ID:1467452

Zhou, Liang ^[1]; Hansen, Charles D. ^[2]

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1. Univ. of Stuttgart (Germany). Visualisierungsinstitute; Univ. of Utah, Salt Lake City, UT (United States)
2. Univ. of Utah, Salt Lake City, UT (United States). Scientific Computing and Imaging (SCI) Inst. and School of Computing

Colormaps are a vital method for users to gain insights into data in a visualization. With a good choice of colormaps, users are able to acquire information in the data more effectively and efficiently. In this survey, we attempt to provide readers with a comprehensive review of colormap generation techniques and provide readers a taxonomy which is helpful for finding appropriate techniques to use for their data and applications. Specifically, we first briefly introduce the basics of color spaces including color appearance models. In the core of our paper, we survey colormap generation techniques, including the latest advances in the field by grouping these techniques into four classes: procedural methods, user-study based methods, rule-based methods, and data-driven methods; we also include a section on methods that are beyond pure data comprehension purposes. We then classify colormapping techniques into a taxonomy for readers to quickly identify the appropriate techniques they might use. Furthermore, a representative set of visualization techniques that explicitly discuss the use of colormaps is reviewed and classified based on the nature of the data in these applications. Lastly, our paper is also intended to be a reference of colormap choices for readers when they are faced with similar data and/or tasks.

• Research Organization: Univ. of Utah, Salt Lake City, UT (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: NA0002375; SC0007446
• OSTI ID: 1467452
• Journal Information: IEEE Transactions on Visualization and Computer Graphics, Journal Name: IEEE Transactions on Visualization and Computer Graphics Journal Issue: 8 Vol. 22; ISSN 1077-2626
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
Color
colormap
perception
survey
visualization