HELMLAB: An Analytical, Data-Driven Color Space for Perceptual Distance in UI Design Systems
This work provides a more perceptually uniform color space for UI designers, addressing the challenge of consistent color perception in digital interfaces, which is an incremental improvement for the field of color science and UI design.
This paper introduces HELMLAB, a 72-parameter analytical color space designed for UI design systems. It maps CIE XYZ to a perceptually organized Lab representation and achieves a STRESS of 23.30 on the COMBVD dataset, representing a 20.2% reduction from CIEDE2000's 29.18. Additionally, a blue-band refit improved blue-cyan gradient uniformity by 8.9x.
We present HELMLAB, a 72-parameter analytical color space for UI design systems. The forward transform maps CIE XYZ to a perceptually-organized Lab representation through learned matrices, per-channel power compression, Fourier hue correction, and embedded Helmholtz-Kohlrausch lightness adjustment. A post-pipeline neutral correction guarantees that achromatic colors map to a=b=0 (chroma < 10^-6), and a rigid rotation of the chromatic plane improves hue-angle alignment without affecting the distance metric, which is invariant under isometries. On the COMBVD dataset (3,813 color pairs), HELMLAB achieves a STRESS of 23.30, a 20.2% reduction from CIEDE2000 (29.18). A blue-band refit with sub-dataset penalties reduces gradient non-uniformity in the blue-cyan region by 8.9x at a cost of only +0.08 STRESS. Cross-validation on He et al. 2022 and MacAdam 1974 shows competitive cross-dataset performance. The transform is invertible with round-trip errors below 10^-14. Gamut mapping, design-token export, and dark/light mode adaptation utilities are included for use in web and mobile design systems.