Weighted Geometric Mean (WGM) method: A new chromatic adaptation model

Abstract

The human visual system has undergone evolutionary changes to develop sophisticated mechanisms that enable stable color perception under varying illumination. These mechanisms are known as chromatic adaptation, a fundamental aspect of color vision. Chromatic adaptation can be divided into two categories: sensory adaptation, which involves automatic adjustments in the visual system, such as retinal gain control, in response to changes in the stimulus, and cognitive adaptation, which depends on the observer’s knowledge of the scene and context. The geometric mean has been suggested to be the fundamental mathematical relationship that governs peripheral sensory adaptation. This paper proposes the WGM model, an advanced chromatic adaptation model based on a weighted geometric mean approach that can anticipate incomplete adaptation as it moves along the Planckian or Daylight locus. Compared with two other chromatic adaptation models (CAT16 and vK20), the WGM model is tested with different corresponding color data sets and found to be a significantly improvement while also predicting degree of adaptation (sensory and cognitive adaptation) in a physiologically plausible manner.