RGBn

RGBn is a generalized color representation that extends the conventional RGB color model by using n primary color channels instead of three. In this framework, the first three channels are typically designated R, G, and B, while the remaining channels (R2, G2, B2, or other identifiers) serve as additional primaries. The concept is used to describe imaging and display systems that employ more than three primary colors to reproduce a broader or more accurate range of perceptible colors.

Mathematically, a color in RGBn is a vector p in R^n containing the channel values, and a device- or scene-referred color c in a 3D perceptual space (often XYZ) is obtained by a linear transformation c = A p, where A is a 3x n matrix that encodes how the primaries map to the chosen reference space. When gamma correction and nonlinear transfer functions are included, the transformation becomes nonlinear. Converting RGBn colors to standard color spaces requires knowledge of the primaries’ spectral properties and their color-matching functions.

Advantages of RGBn include expanded gamut coverage, improved color accuracy for broad-spectrum scenes, and greater flexibility in device calibration and spectral imaging. Potential drawbacks are increased system complexity, calibration demands, and challenges in standardization and perceptual uniformity across devices.

Applications and contexts for RGBn include multi-primary displays, high-fidelity lighting design, camera systems with spectral sensing, and research in color science. As a generalization, RGBn reduces to conventional RGB when n equals three.