Edge classification for color constancy

The goal of color constancy is to measure image colors despite differences in the color of the light source. Traditionally, the computational method of obtaining this ability is by using pixel values only. Recently, methods using edges instead of pixel values have been proposed. However, different edge types exist, such as material, shadow and specular edges. Therefore, in this paper, the main goal is to analyze the influence of different edge types on the performance of edge-based color constancy. It is shown that, on generated data without color clipping, specular edges deliver near-perfect color constancy and that shadow edges are more valuable than material edges. However, with color clipping, the performance using the specular edges decreases significantly, while the performance using the material or shadow edges is less affected.