Абстрактный

Specular Edge Weighting for Local Color Correctionof Images

Ancy Varghese, Darsana Vijay

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. Specular edge weighting scheme which works 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. Specular edges are selected for weighting scheme since it contains more information about color values. Experiments show that this method reduces the error when compared with existing local correction methods which uses derivative image structures.