Spatial models of color

Classic colorimetric approach consider color a pointwise information, but this is contraddicted by the perceptual experience. There is a growing family of algorithms that treat color information in its visual context, also known as spatial color methods (e.g. Retinex, ACE). In this work we aim at presenting some common characteristics of these models and their relationship with human color perception. Two main variables affect the final result of these algorithm: their parameters and the visual characteristics of the image they work on. With the term visual characteristics we refer not only to their imaging parameters, like e.g. pixel mean value or used dynamic range, but also to their spatial distribution in the image. A survey of the more significant visual configurations will be presented and discussed, hopefully allowing a deeper understanding of their behavior and stimulating further research directions.