Improving Edge Based Color Constancy for Multiple Light Sources

Color constancy algorithms are used for making illuminant independent images. Illuminant independency is achieved in most of algorithms by uniform light source assumption. But this condition may violate in most of real world images which introduces performance failure in computer vision applications like object tracking and object recognition. Local color correction for up to two light sources has been developed by various algorithms. In this paper derivative structure of images are used for local color correction for up to three light sources. Specular edge weighting scheme on derivative structure of image is applied to grid sampled patches of the image to achieve local color correction. Each estimate from patches is combined and result is projected onto input image so that pixel estimate is obtained. Color correction is achieved on a diagonal model with pixel estimates. Experiments show that specular edge weighting method reduces the error when compared with existing local correction methods which uses derivative image structures.