Color constancy using local color shifts

The human visual system is able to correctly determine the color of objects in view irrespective of the illuminant. This ability to compute color constant descriptors is known as color constancy. We have developed a parallel algorithm for color constancy. This algorithm is based on the computation of local space average color using a grid of processing elements. We have one processing element per image pixel. Each processing element has access to the data stored in neighboring elements. Local space average color is used to shift the color of the input pixel in the direction of the gray vector. The computations are executed inside the unit color cube. The color of the input pixel as well as local space average color is simply a vector inside this Euclidean space. We compute the component of local space average color which is orthogonal to the gray vector. This component is subtracted from the color of the input pixel to compute a color corrected image. Before performing the color correction step we can also normalize both colors. In this case, the resulting color is rescaled to the original intensity of the input color such that the image brightness remains unchanged.