Adaptive transfer of color from images to maps and visualizations

Abstract

Terrain mapping is not only dedicated to communicating how high or how steep a landscape is but can also help to narrate how we feel about a place. However, crafting effective and expressive hypsometric tints is challenging for both nonexperts and experts. In this paper, we present a two-step image-to-terrain color transfer method that can transfer color from arbitrary images to diverse terrain models. First, we present a new image color organization method that organizes discrete, irregular image colors into a continuous, regular color grid that facilitates a series of color operations, such as local and global searching, categorical color selection and sequential color interpolation. Second, we quantify a series of subjective concerns about elevation color crafting, such as "the lower, the higher" principle, color conventions, and aerial perspectives.We also define color similarity between image and terrain visualization with aesthetic quality. We then mathematically formulate image-to-terrain color transfer as a dual-objective optimization problem and offer a heuristic searching method to solve the problem. Finally, we compare elevation tints from our method with a standard color scheme on four test terrains. The evaluations show that the hypsometric tints from the proposed method can work as effectively as the standard scheme and that our tints are more visually favorable. We also showcase that our method can transfer emotion from image to terrain visualization.

Light mode and dark mode: Which one is suitable when using public‐facing web maps? An experimental evaluation using eye‐tracking

“…Such as the map mode with strong color contrast is conducive to the separation of figure and ground and enhances the shape of the feature. Second, as an aesthetic element, color is used to increase visual pleasure (Wu et al, 2021). Thus, light and dark modes influence the aesthetic of maps.…”

“…Second, we did not consider the color preferences or impaired vision of users. Users have different preferences for color due to different cultural and regional backgrounds (Wu et al, 2021). For example, children may prefer highly saturated colors because their visual perception systems are not well developed.…”

Digital maps burn huge carbon

“…S8). Third, inspiration-based adjustment: Considering that digital maps typically consume more energy than traditional paintings, low-energy color palettes can be transferred from paintings to digital maps for energy savings 29,30 . By taking inspiration from low-energy paintings, visually appealing energy-saving maps can be created.…”