Simple constraints on the sets of possible surface reflectance and illuminants are exploited in a new color constancy algorithm that builds upon Forsyth's (1990) theory of color constancy. Forsyth's method invokes the constraint that the surface colors under a canonical illuminant all fall within an established maximal convex gamut of possible colors. However, the method works only when restrictive conditions are imposed on the world: the illumination must be uniform, the surfaces must be planar, and there can be no specularities. To overcome these restrictions, we modify Forsyth's algorithm so that it works with the colors under a perspective projection (in a chromaticity space). The new algorithm working in perspective is simpler than Forsyth's method and more importantly the restrictions on the illuminant, surface shape and specularities can be relaxed. The algorithm is then extended to include a maximal gamut constraint on a set of illuminants that is analogous to the gamut constraint on surface colors. Tests on real images show that the algorithm provides good color constancy.
|Number of pages||5|
|Journal||IEEE Transactions on Pattern Analysis and Machine Intelligence|
|Publication status||Published - 1996|