When light enters the eye and hits the retina, it’s processed in many layers of neurons and creates a mental impression. It’s unlikely that the process would be simple and linear, and it’s not. But incredibly enough, most people still perceive colors similarly.

People have been trying to understand colors and have created color wheels and similar visualizations for hundreds of years. During the 20th century, a lot of research and modeling went into color vision. For example, the CIE XYZ model is based on how sensitive our photoreceptor cells are to different frequencies of light. CIE XYZ is still a foundational color space on which all other color spaces are based.

There were also attempts to create simple models matching human perception based on XYZ, but as it turned out, it’s not possible to model all color vision that way. Perception of color is incredibly complex and depends, among other things, on whether it is dark or light in the room and the background color it is against. When you look at a photograph, it also depends on what you think the color of the light source is. The dress is a typical example of color vision being very context-dependent. It is almost impossible to model this perfectly.

Models that try to take all of this complexity into account are called color appearance models. Although they have many applications, they’re not that useful if you don’t know if the viewer is in a light or bright room or other viewing conditions.

The odd thing is that there’s a gap between the tools we typically use — such as sRGB and HSL — and the findings of this much older research. To an extent, this makes sense because when HSL was developed in the 1970s, we didn’t have much computing power, so it’s a fairly simple translation of RGB. However, not much has changed since then.