Photographic High-Dynamic-Range Scalar Visualization

Abstract

We propose a photographic method to show scalar values of high dynamic range (HDR) by color mapping for 2D visualization. We combine (1) tone-mapping operators that transform the data to the display range of the monitor while preserving perceptually important features, based on a systematic evaluation, and (2) simulated glares that highlight high-value regions. Simulated glares are effective for highlighting small areas (of a few pixels) that may not be visible with conventional visualizations; through a controlled perception study, we confirm that glare is preattentive. The usefulness of our overall photographic HDR visualization is validated through the feedback of expert users.

Data-Driven Colormap Adjustment for Exploring Spatial Variations in Scalar Fields

“…Our ROI interactive functionality is a way to address this problem, but it requires manual operations. Two possible automatic solutions are either introducing visibility analysis [47], or adding new colors into the colormap adjustment framework [28], [32]. We provided a fidelity term to avoid significant color changes between the input and adjusted colormaps, whose effect on the final visualization can be tuned through a balancing weight.…”

“…Several methods use image processing operators to enhance colormap design [29], [30], [31], [32], so that the improved visualization resolves more information. Zhou et al integrate view distance into the contrast enhancement process [30], and then propose a visualization sharpening scheme based on the power spectrum [31].…”

“…However, their methods directly enhance images and, thus, cannot preserve one-to-one mappings between the data and colormap. Following their previous work, Zhou et al [32] propose a color enhancement method for high-dynamic-range data based on tone mapping techniques and glare simulation. Though they leverage a global tone mapping scheme to ensure one-to-one mappings between the data and colors, their modification of the input data may hinder accurate understanding of the data values.…”

Visual Analysis of Traditional Chinese Medicine Health Records

“…例如, 使用颜 色和纹理对多维数据进行可视化 [27] . 近来, 通过 感知实验验证的特别设计的前注意视觉元素已被 运用在高动态范围标量数据可视化 [28] 和虚拟现实 环境中的可视化领域 [29][30] .…”

2020 Index IEEE Transactions on Visualization and Computer Graphics Vol. 26

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