daltonizer

Daltonizer is a term used in color science and accessibility to describe software or hardware that applies a color transformation to digital imagery or display output in order to simulate color vision deficiency (color blindness) or to compensate for it by making colors more distinguishable. The name derives from John Dalton, who first described color blindness in the early 19th century, and the practice of daltonization refers to adjusting colors to be perceivable by color-blind individuals.

Two primary uses exist: simulation and correction. In simulation mode, daltonization maps colors to approximate how a color-blind observer would perceive them, typically for prototyping and testing color palettes. In correction mode, the aim is to alter colors in a scene so that individuals with common deficiencies (protanope, deuteranope, or tritanope) can distinguish them, often by augmenting color differences while preserving perceived brightness.

Algorithms often operate in perceptual color spaces such as LMS or CIELAB and may involve transformations that emulate cone responses. Widely cited models for simulation include variants developed to mimic protanopia, deuteranopia, and tritanopia. Daltonization can also be implemented as palette remapping, where colors are shifted within a safe color gamut to maintain luminance contrast.

Common deficiencies addressed include protanopia, deuteranopia, and tritanopia, as well as anomalous trichromacy. The tool is used by designers, educators, and software developers to improve accessibility, in image editing, game design, and user interface testing. Limitations include approximation, device-dependent results, and the fact that not all individuals with color vision variation are covered by a single model.