rgb2oklab: RGB to Perceptual Color Space Conversion

Mathematical Foundation of Perceptual Color Encoding

RGB to OKLab conversion transforms linear RGB values into a perceptually uniform color space where equal numerical distances represent equal perceived color differences. The transformation involves two matrix operations with intermediate cube root processing.

The mathematical operation sequence: $\text{LMS} = M_B \cdot \text{RGB}$ $\text{OKLab} = M_A \cdot \sqrt[3]{\text{LMS}}$

Where $M_B$ transforms RGB to LMS cone response values, the cube root operation compresses the light response to match human perception, and $M_A$ produces the final OKLab coordinates.

Perceptual Properties

OKLab coordinates encode color information optimally for human vision. The L component represents perceived lightness, while a and b components encode green-red and blue-yellow color opponents respectively. This structure aligns with human visual processing pathways.

Mathematical characteristics:

• Cube root compression: Models logarithmic light sensitivity of human vision
• Cone space mapping: LMS coordinates correspond to human photoreceptor responses
• Uniform perception: Color differences in OKLab correlate with visual perception

ライブエディター

const fragment = () => {
      const rgbColor = vec3(uv.x, uv.y, 0.6)
      const oklabColor = rgb2oklab(rgbColor)
      return vec4(oklabColor.mul(0.5).add(0.5), 1)
}