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.

翻译：本文提出HELMLAB，一种面向UI设计系统的72参数解析色彩空间。其前向变换通过学习矩阵、逐通道幂压缩、傅里叶色调校正及嵌入式亥姆霍兹-科赫劳施明度调整，将CIE XYZ映射至感知组织的Lab表示。后处理中性色校正确保非彩色映射至a=b=0（色度<10^-6），而色度平面的刚性旋转在保持距离度量（在等距变换下不变）的同时改善了色调角对齐。在COMBVD数据集（3,813个色彩对）上，HELMLAB的STRESS指标为23.30，较CIEDE2000（29.18）降低20.2%。通过子数据集惩罚的蓝波段重新拟合，将蓝-青区域的梯度不均匀性降低8.9倍，仅增加+0.08 STRESS。基于He等人（2022）与MacAdam（1974）数据的交叉验证显示了优异的跨数据集性能。该变换具有可逆性，往返误差低于10^-14。空间同时包含色域映射、设计令牌导出及深色/浅色模式适配工具，适用于网页与移动端设计系统。