"A color space is perceptually uniform if a change of length in any direction X of the color space is perceived by a human as the same change. Non-uniform perceptual color spaces like RGB and RYB can have stark contrasts when transitioning from one hue to another hue. In data visualization, these contrasts can be mistaken as changes in the data rather than as transitions in the color palette."
"As a result, many data visualization practitioners prefer to work in the perceptual uniform CIE LAB or Hue Chroma Luminance (HCL) color spaces. Unfortunately, these color spaces have irregularly shaped geometries resulting in challenges to calculate color combinations that also pass color deficiency. Gen AI systems, like Microsoft Copilot, can help to quickly locate these perceptual uniform color schemes for data visualization. Let's begin our journey by first defining the concepts of triad color harmony, perceptual uniformity, and color deficiency."
Triad color harmony selects three hues evenly spaced around a color wheel to create balanced palettes. A color space is perceptually uniform if equal geometric distances produce equal perceived changes in color. Non-uniform spaces like RGB and RYB introduce stark visual contrasts across hue transitions that can be misread as data variation in visualizations. Perceptually uniform spaces such as CIE LAB and Hue Chroma Luminance (HCL) minimize perceptual distortion but have irregular geometries. Their irregular shapes make calculating triads that also satisfy color-deficiency accessibility difficult. Generative AI systems can assist by rapidly locating perceptually uniform triads that maintain both uniformity and accessibility.
#perceptual-color-spaces #color-deficiency-accessibility #generative-ai #data-visualization #color-harmony
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