Daltonization

Daltonization, also spelled daltonisation, is a family of image-processing techniques that modify color information to improve visibility for people with color vision deficiencies. The term derives from Daltonism, the historical name for color blindness, and the methods aim to make color differences more distinguishable rather than simply simulating how colors appear to affected viewers.

The goal of daltonization is to preserve perceptual distinctions for color-blind observers while maintaining overall image fidelity for those with normal color vision. In practice, algorithms often perform a two-step process: first estimate how a viewer with a deficiency would perceive the original image using a color-vision model, and then adjust colors to maximize separability in that deficient perception. Some approaches directly map colors into a chromatic space or use perceptually informed transformations to increase contrast between similar hues that would be confused by a color-blind viewer.

Common methods rely on color-space concepts that approximate cone responses or perceptual uniformity. Techniques may adjust hue, saturation, and luminance to reduce color collisions (where distinct colors become indistinguishable under a deficiency) while striving to keep the image recognizable to viewers with normal vision. In some designs, daltonization is combined with the creation of color-blind–friendly palettes or with dynamic rendering that adapts to the viewer’s needs.

Daltonization is used in information graphics, maps, charts, web design, and educational materials to enhance accessibility. It supports inclusive visual communication by helping ensure important distinctions remain visible to people with color vision deficiencies.